Update: Due to concerns surrounding the spread of the novel coronavirus (COVID-19), we have made the decision to postpone indefinitely our Biomedical Course Week scheduled for March 24-26.

While we are disappointed that we are not able to offer these courses at this time, we are committed to following the guidance of health officials and preserving the wellbeing of our valued employees, communities, customers, and collaborators.

We will keep you informed of new opportunities to learn about Kitware’s software platforms, including future courses.

We appreciate your support and understanding and look forward to another opportunity to engage with you in the future.

The International Association for Dental Research (IADR), celebrating its centennial this year, will host its 98th General Session and Exhibit March 18-21 in Washington, D.C. This event is the leading scientific meeting for dental, oral, and craniofacial research.

Kitware is pleased to have Technical Leader Beatriz Paniagua host a workshop during the conference. The workshop focuses on SlicerSALT, a free, open source software platform that allows biomedical scientists to precisely locate shape changes in their imaging studies. During the workshop, attendees will learn how to use SlicerSALT for dental research. 

Below is more detailed information about the workshop:

Shape Analysis in Dental Imaging Research Using SlicerSALT

Presented by: Kitware Technical Leader Beatriz Paniagua

Presentation Date: Friday, March 20

Session Time: 2:00 PM – 3:30 PM

To learn more about Kitware’s medical computing work, please reach out to kitware@kitware.com. 

The SlicerSALT developers gratefully acknowledge funding for this project provided by NIH NIBIB R01EB021391 (Shape Analysis Toolbox for Medical Image Computing Projects), as well as the Slicer community.

Kitware is proud to sponsor the 2020 Winter Conference on Applications of Computer Vision in Aspen, CO, March 2-5, 2020. Join us as we meet to support the community, recruit computer vision professionals, and continue collaboration and engagement.

Details:

Kitware is a Gold Sponsor of WACV’20.

Dr. Anthony Hoogs, senior director of computer vision, will present one of the six workshops hosted at WACV on Thursday, March 5: Human Activity Detection in Multi-Camera, Continuous, Long-Duration Video.

On Wednesday, March 4, Senior R&D Engineer Dr. Chengjiang Long and R&D Engineer Bhavan Vasu will present a paper: Iterative and Adaptive Sampling with Spatial Attention for Black-Box Model Explanations.

Please visit our computer vision webpage for more information about our key focus areas and experience.

Contact:

Please reach out to computervision@kitware.com to schedule meetings throughout this event.

About WACV:

WACV is known as the IEEE’s and the PAMI-TC’s premier meeting on applications of computer vision. Taking place at The Westin Snowmass Resort in Snowmass Village, the conference will include workshops, tutorials and main sessions.  Each year, WACV continues to grow with active participation by academia, industry, and government representatives. The event provides in-depth information on cutting edge research advances in applications of computer vision technology.  Topics such as biometrics, deep learning, action recognition, surveillance, 3D reconstruction, tracking, detection, and vision and learning will be discussed in various formats such as presentations, poster sessions, and forums. This venue promotes collaboration, research and development, and insight into computer vision applications and technology.

The Ocean and Sciences Meeting in San Diego is the premier research conference for the ocean sciences and ocean-connected community. The conference brings together scientists from around the world to discuss all aspects of oceanography, providing a valuable opportunity for the community to exchange ideas, information, and new research affecting the field.  

Kitware is proud to have two papers included in the conference. Each paper centers around Video and Imagery Analysis for the Marine Environment (VIAME), an open source software toolkit Kitware developed in partnership with the NOAA National Marine Fisheries Service through its Automated Imagery Analysis Strategic Initiative. VIAME uses artificial intelligence (AI) to enable fisheries biologists and other marine scientists at NOAA and laboratories around the world to automatically analyze large volumes of imagery and video for scientific studies, such as estimating the population of fish species in a fishery.

The requirements, capabilities, and development of VIAME were funded and overseen by the AIASI Steering Committee, which included members from each of the six NMFS Science Centers as well as Dr. Anthony Hoogs from Kitware.

VIAME has gained notable recognition, including a Gold Medal Award for Scientific or Technical Achievement from the Department of Commerce. This is the most prestigious honor given by the Department of Commerce each year.  

Below is more detailed information about each paper presentation:

An Open-Source System for Do-It-Yourself AI in the Marine Environment

Presented by: Kitware’s Senior Director of Computer Vision, Dr. Anthony Hoogs

Date and Time: Thursday, February 20 at 4 p.m. PT

Authors: Anthony Hoogs, Matthew Dawkins, Benjamin Richards (NOAA), George Cutter (NOAA), Deborah Hart (NOAA), M. Elizabeth Clarke (NOAA), William Michaels (NOAA), Jon Crall, Linus Sherrill, Neil Siekierski, Matthew Woehlke, Kyle Edwards

Moving Towards Machine Learning for the Analysis of Deep-Sea Imagery Collected by Autonomous Underwater Vehicle

Presented by: Abigail Powell of NOAA Northwest Fisheries Science Center

Date and Time: Thursday, February 20 at 9:30 a.m. PT

Authors: Abigail Powell (NOAA), M. Elizabeth Clarke (NOAA), Matthew Dawkins, Benjamin Richards (NOAA), Anthony Hoogs

To learn more about Kitware’s computer vision work, or to schedule meetings with Anthony Hoogs and Matt Dawkins at the event, please reach out to computervision@kitware.com.  We look forward to engaging with this community and sharing information about Kitware’s ongoing research and capability development in computer vision and deep learning, as well as our cutting-edge open source software.

This year, Kitware is excited to be included in the main program of the Thirty-Fourth Association for the Advancement of Artificial Intelligence (AAAI) Conference on Artificial Intelligence (AAAI-20) taking place February 17-21, 2020 in New York. This prestigious, highly selective conference has been growing more than 25% per year due to its focus on fostering scientific exchange between researchers, practitioners, scientists, students, and engineers in artificial intelligence (AI) and its affiliated disciplines.  As the premier international conference in general AI, AAAI has a very low acceptance rate of 20%, with a rigorous review and selection process that ensures all selected papers meet the highest academic research standards. Kitware will present at the conference on February 9, and will also be at the AAAI job fair on February 11 between 12:30 and 3 PM ET to discuss opportunities to join Kitware’s Computer Vision Team.

Kitware’s Senior R&D Engineer, Chengjiang Long, Ph.D., will present a  paper: RIS-GAN: Explore Residual and Illumination with Generative Adversarial Networks for Shadow Removal. The paper was authored by Ling Zhang, Ph.D., Chengjiang Long, Ph.D., Xiaolong Zhang, Ph.D., and Chunxia Xiao, Ph.D. to explore cutting edge techniques that address the challenging problems with removing shadows in complex scenes. These shadows negatively impact the accuracy and effectiveness of many computer vision tasks and the need for more effective techniques to remove them or mitigate their impact has been increasing exponentially. Chengjiang will provide a detailed look at the research and extensive experiments, with results, that strongly confirm the advantages of incorporating residual and illumination foreshadow removal.  

Details About the Presentation:

Sunday, February 9

11:15 a.m. – 12:30 p.m. ET

Spotlight Session #151 (Vision Synthesis and Generation)

Paper ID 4545

Chengjiang will also participate in the evening poster session on February 9 from 7:30 to 9:30 p.m. ET for more in-depth, face-to-face discussions related to this work. 

Kitware’s Computer Vision Team is dedicated to pushing research and technology development to better understand and utilize artificial intelligence (AI). We have a long-standing history in computer vision and deep learning. An early convert to deep learning, we have been developing expertise and tools to support deep learning technologies and techniques for years. Please visit our computer vision webpage for more information about our key focus areas and experience.

About AAAI:

AAAI’s annual conference attracts over 3,000 AI researchers and practitioners, representing government, university, and corporate research facilities from throughout the world. The conference features a diverse technical track, student abstracts, poster sessions, invited speakers, tutorials, workshops, and exhibit and competition programs, all selected according to the highest reviewing standards.  In 2020, AAAI will highlight research with a special track on artificial intelligence for social impact.

Are you attending the International Meeting on Simulation in Healthcare? Join us January 18-22, 2020 at Kitware booth #912 and speak with Dr. Rachel Clipp, Aaron Bray, and Sreekanth Arikatla from our Medical Computing team.

Learn about our leading medical research and development software platforms, including Pulse, iMSTK and 3D Slicer. We’ll have interactive VR demos and videos to demonstrate the value these software tools create for medical training.

And don’t miss our presentation and Pulse demo during the SimVentors Showcase at 6 p.m. on Sunday, January 19!

Visit Kitware at SC19 Booth #2019

Join the Kitware team at SC19 booth 2019 Monday, November 18, to Thursday, November 21. Expert ParaView, VTK and CMake developers will be opening up the floor for questions and discussion. And don’t miss an opportunity to grab giveaways and hear about our latest projects during our booth talks and demos!

Booth Talks

Monday, November 18
What’s New at Kitware? 
7 p.m. • Dave DeMarle

Tuesday, November 19
From ParaView to Your Browser to Your VR Headset
11:15 a.m. • Sébastien Jourdain

Catalyst for Analysis and Visualization in Extreme Scale Computing
11:45 a.m. • Patrick O’Leary

Introduction to ParaView
1:15 p.m. • Cory Quammen

Ray Tracing Update
1:45 p.m. • Dave DeMarle

What’s New in CMake?
2:15 p.m. • Rob Maynard

HPC Cloud Services to Enable a Cloud/Web-Based Simulation Environment
2:45 p.m. • Patrick O’Leary

Visualization and Data Processing on the Web
3:15 p.m. • Sébastien Jourdain

CMB/SMTK
3:45 p.m. • David Thompson

Wednesday, November 20
CMB/SMTK 
11:15 a.m. • David Thompson

Catalyst for Analysis and Visualization in Extreme-Scale Computing
11:45 a.m. • Patrick O’Leary

Introduction to ParaView
1:15 p.m. • Cory Quammen

Supercomputing with ParaView – featuring CRAY
1:45 p.m. • Chuck Atkins

What’s New in CMake?
2:15 p.m. • Rob Maynard

From ParaView to Your Browser to Your VR Headset
2:45 p.m. • Sébastien Jourdain

Visualization and Data Processing on the Web
3:15 p.m. • Sébastien Jourdain

Team Members

• Bill Hoffman, chief technical officer
• Patrick O’Leary, assistant director of scientific computing
• Dave DeMarle, principal engineer
• Sebastien Jourdain, principal engineer
• Rob Maynard, principal engineer
• Chuck Atkins, staff R&D engineer
• Patrick Avery, R&D engineer
• David Thompson, staff R&D engineer
• Omar Padron, senior R&D engineer
• Caitlin Ross, R&D engineer
• Sankhesh Jhaveri, senior R&D engineer
• Cory Quammen, staff R&D engineer
• John Westbrook, human resources generalist
• Libby Rose, business development representative

Hiring

If you are interested in working on VTK and/or ParaView as a member of our team, please let us know when you stop by our booth or see us at one of the activities in which we are involved. For more information on our jobs or work environment, please visit https://jobs.kitware.com.

Activities

Sunday, November 17
Catch Robert Robert Maynard and Dave DeMarle at Intel’s HPC Developer Conference:

• 10:30-10:55 a.m. Rob Maynard will lead the CMake: Build Your World tutorial
• 2:45-3:15 p.m. Dave DeMarle will present OSPRay 2.0, Optane, and ParaView-VTK-Catalyst Integration Update

Tuesday, November 19
Join us at our booth for a ParaView Power Hour taking place at 1 p.m. A rare opportunity to ask your questions about ParaView face to face with our experts!

Visit the NVIDIA Booth (#901) to hear Rob Maynard and NIVIDIA’s Peter Messmer present RTX and Omniverse from 4:30-4:55 p.m

Wednesday, November 20

Join us for a  CMake Power Hour taking place at 2 p.m. at our booth. Don’t miss this rare opportunity to meet our experts face to face and ask your questions about CMake!

Join Kitware CEO Lisa Avila, and other members of the Kitware team, November 7-9 at the world’s largest conference for women engineers – WE19!

Stop by the Kitware booth (#214) to meet our team and find out what life at Kitware is all about.

Plus, you won’t want to miss Lisa’s presentation, “The Open Business Model: Running an IP-Free Business,” happening Saturday, November 9 at 10:40 a.m. Here are some additional details:

You’ve founded a company based on your passion for innovation and your desire to make an impact. It is great fun developing the new technology, but then you have to file patents, protect your IP, worry about competitors, focus on marketing, and drive sales. Instead, you can choose to run an IP-free organization by being in the business of innovating new technology instead of selling your existing technology. While this may not lead to a lucrative IPO or a sweet acquisition deal, it does help with recruiting and employee engagement, it reduces your need for a sales force and it generally results in a more personally rewarding experience. With an IP-free business, you are free to collaborate with anyone and publish your work, which significantly increases your impact and ultimately helps your bottom line.

Attendees at the show:

Lisa Avila, CEO

Rachel Clipp, technical leader

Bea Paniagua, technical leader

Heather James, manager, innovative applications

John Westbrook, human resources generalist

We hope to see you in Anaheim!

Dave DeMarle will lead a VTK hackathon focusing on packaging. Join us as we work to make sure the VTK library is easier for end-users to get and to start using.

The hackathon will take place November 6, from 9 a.m. to 4 p.m. ET. Join in person at our HQ in Clifton Park, NY or via Google Hangout.

Follow updates and join the conversation beforehand on our discourse thread.

Join Kitware’s Computer Vision Team at this year’s International Conference on Computer Vision 2019, taking place October 27-November 2 in Seoul, Korea!

Details:

Kitware will also have a presence during the main conference. On Friday, November 1 at 3:30 p.m. (15:30), Senior R&D Engineer Dr. Chengjiang Long will present the poster “ARGAN: Attentive Recurrent Generative Adversarial Network for Shadow Detection and Removal.”  The purpose is to propose an attentive recurrent generative adversarial network (ARGAN) to detect and remove shadows in an image. The generator consists of multiple progressive steps, which Dr. Long will detail.  ARGAN is suitable to be trained with a semi-supervised strategy to make full use of sufficient unsupervised data, which can be very challenging. Come learn more about this robust model and where this work will extend to for future development and implementation addressing shadow detection and removal. 

Contact:

Please reach out to computervision@kitware.com to schedule meetings throughout this event.  Find out about Kitware’s computer vision research and capability development supporting academia, defense, environmental monitoring, and commercial domains.

About the event:

ICCV is the premier international computer vision event combining high quality tutorials, workshops, and the main exhibition in order to fuel collaboration amongst students, academics, and industry researchers worldwide. The value in attending is exponential as it provides international perspectives on vision techniques, research & development, open-source software, and their current and potential contributions to various domains.

Join Kitware’s Computer Vision Team at this year’s International Conference on Computer Vision 2019, taking place October 27-November 2 in Seoul, Korea!

Details:

Kitware will also have a presence during the main conference. On Friday, November 1 at 3:30 p.m. (15:30), Senior R&D Engineer Dr. Chengjiang Long will present the poster “ARGAN: Attentive Recurrent Generative Adversarial Network for Shadow Detection and Removal.”  The purpose is to propose an attentive recurrent generative adversarial network (ARGAN) to detect and remove shadows in an image. The generator consists of multiple progressive steps, which Dr. Long will detail.  ARGAN is suitable to be trained with a semi-supervised strategy to make full use of sufficient unsupervised data, which can be very challenging. Come learn more about this robust model and where this work will extend to for future development and implementation addressing shadow detection and removal. 

Contact:

Please reach out to computervision@kitware.com to schedule meetings throughout this event.  Find out about Kitware’s computer vision research and capability development supporting academia, defense, environmental monitoring, and commercial domains.

About the event:

ICCV is the premier international computer vision event combining high quality tutorials, workshops, and the main exhibition in order to fuel collaboration amongst students, academics, and industry researchers worldwide. The value in attending is exponential as it provides international perspectives on vision techniques, research & development, open-source software, and their current and potential contributions to various domains.

Kitware will be presenting at this year’s Military Sensing Symposia (MSS) Joint Conference  in San Diego, CA, October21-24. We have actively participated in this conference each year as it is dedicated to military sensing technologies. Kitware’s Computer Vision Team is a leader in creating cutting edge capabilities supporting this community focused on military sensing.  We create unique and robust solutions to address challenging image and video analysis problems in multiple domains: air, sea, ground, and space.

Event Details:

Join Dr. Matt Leotta and Dr. Chris Funk from Kitware’s Computer Vision Team as they present the following at this year’s MSS Conference:

Danesfield: Integrating Deep Learning and Classical Methods for Multiview Semantic 3D Modeling (Presentation): Dr. Matt Leotta will discuss the importance of up-to-date 3D models of urban environments, as they are very important in providing global situational awareness with uses in military, intelligence, and humanitarian planning.  Kitware has worked with the IARPA CORE3D program and developed and open source toolkit, known as Danesfield, to address this need for 3D models, pushing it beyond just point clouds by semantically segmenting building and bridges from the terrain and fitting simplified surface models to each object.  They also explore material segmentation providing more robust situational awareness and knowledge of scene. Come check out Dr. Leotta’s discussion to learn more or visit our Github to check it out.

Explainability for Content-Based Image Retrieval (Poster): Make sure to also check out Dr. Leotta’s poster in the poster sessions and hear him discuss Kitware’s methods for content-based image retrieval and where our expertise and past projects have contributed to robust and explainable solutions supporting the military sensing community.

WEFT Feature Detection and Mensuration for Airplane Classification in Satellite Imagery (Presentation): Dr. Chris Funk, a member of the computer vision team, will discuss our work building upon state-of-the-art techniques object classification, which overcomes hurdles particular to airplane classification.  It consists of classifying by first detecting intermediate WEFT features and measuring and fusing those features together. This allows for detection of airplanes in satellite imagery, not in the training data, and avoids class imbalance.  Kitware’s efforts have been supported by multiple, ongoing efforts funded by the DoD and Intelligence Community (IC).

Training Deep Networks for Patch-Based Search in Satellite Imagery (Poster): Dr. Funk will also be presenting Kitware’s extensive research in the area of content-based image retrieval.  He will discuss specific challenges of retrieving relevant results from large, high-resolution imagery based on arbitrary queries at a range of scales.  It presents significant complications beyond common image retrieval tasks and this discussion will offer a working end-to-end description of a system for this kind of extensive patch-based search on real-world satellite imagery.

Contact:

Please reach out to computervision@kitware.com to schedule meetings throughout this event.  Matt Leotta and Chris Funk will be on-hand for in depth conversations.  We are looking forward to engaging with this community and sharing information on Kitware’s ongoing research and capability development in computer vision and deep learning as well as our cutting-edge open source vision software, KWIVER.

About the event:

The Military Sensing Symposia is a set of conferences dedicated to military sensing technologies and serving the community of people working in those fields.

VIS 2019 will be the year’s premier forum for advances in theory, methods, and applications of visualization and visual analytics. The conference will convene an international community of researchers and practitioners from universities, government, and industry to exchange recent findings on the design and use of visualization tools.

Kitware’s Director of Medical Computing Andinet Enquobahrie and Senior Director of Strategic Initiatives Stephen Aylward will present at the International Conference on Medical Image Computing and Computer Assisted Intervention.

Development and Face Validation of Ultrasound-Guided Renal Biopsy Virtual Trainer

To be presented at a joint workshop MIAR, AE-CAI and CARE

The 7th International Conference on Medical Imaging and Augmented Reality (MIAR)
The 13th Augmented Reality, Augmented Environments for Computer Assisted Interventions (AE-CAI),
and 6th Computer Assisted and Robotic Endoscopy (CARE)

https://workshops.ap-lab.ca/aecai-care-miar-2019/

Abstract: The overall prevalence of chronic kidney disease (CKD) in the general population is approximately 14 percent with more than 661,000 Americans having a kidney failure. Ultrasound-guided renal biopsy is a critically important tool in the evaluation and management of renal pathologies and it requires competent biopsy technique and skill to consistently obtain high yield biopsy samples. This paper presents KBVTrainer, a virtual simulator that we developed to train clinicians to improve procedural skill competence in ultrasound-guided renal biopsy. The simulator was built using low-cost hardware components and open source software libraries. We conducted a face validation study with five experts who were either adult/pediatric nephrologists or interventional/diagnostic radiologists. All the experts had considerable experience performing US guided needle biopsies within their specialty with experience ranging from 3-23 years. The trainer was rated very highly (>4.4) for the usefulness of the real US images (highest at 4.8), potential usefulness of the trainer in training for needle visualization, tracking, steadiness and hand-eye coordination, and overall promise of the trainer to be useful for training US guided needle biopsies. The lowest score of 2.4 was received for the look and feel of the US probe and needle compared to clinical practice. The force feedback received a moderate score of 3.0. The clinical experts provided abundant verbal and written subjective feedback and were highly enthusiastic about using the trainer as a valuable tool for future trainees. As part of the future work, we will improve the technology based on clinical and user feedback, develop automated skill assessment and tracking modules deployable in a web-based application, and conduct a clinical validation study.

Active Learning Technique for Multimodal Brain Tumor Segmentation using Limited

To be presented at Medical Image Learning with Less Labels and Imperfect Data

https://www.hvnguyen.com/lesslabelsimperfectdataml

Abstract: Image segmentation is an essential step in biomedical image analysis. In recent years, deep learning models have achieved significant success in segmentation. However, deep learning requires the availability of large annotated data to train these models, which can be challenging in biomedical imaging domain. In this paper, we aim to accomplish biomedical image segmentation with limited labeled data using active learning. We present a deep active learning framework that selects additional data points to be annotated by combining U-Net with an efficient and effective query strategy to capture the most uncertain and representative points. This algorithm decouples the representative part by first finding the core points in the unlabeled pool and then selecting the most uncertain points from the reduced pool, which are different from the labeled pool. In our experiment, only 13% of the dataset was required with active learning to outperform the model trained on the entire 2018 MICCAI Brain Tumor Segmentation (BraTS) dataset. Thus, active learning reduced the amount of labeled data required for image segmentation without a significant loss in the accuracy.

Intramodality Domain Adaptation using Self Ensembling and Adversarial Training

To be presented at Domain Adaptation and Representation Transfer (DART) workshop

https://sites.google.com/view/dart2019/

Abstract. Advances in deep learning techniques have led to compelling achievements in medical image analysis. However, performance of neural network models degrades drastically if the test data is from a domain different from training data. In this paper, we present and evaluate a novel unsupervised domain adaptation(DA) framework for semantic segmentation which uses self ensembling and adversarial training methods to effectively tackle domain shift between MR images. We evaluate our method on two publicly available MRI dataset to address two different types of domain shifts: On the BraTS dataset to mitigate domain shift between high grade and low grade gliomas and on the SCGM dataset[13] to tackle cross institutional domain shift. Through extensive evaluation, we show that our method achieved favorable results on both datasets.

“Proposal Writing 101” at the MICCAI “Tutorial On Publishing, GRant writing And career Development” (TOPGRAD) workshop

Presented by Kitware’s Senior Director of Strategic Initiatives Stephen Aylward on October 13th

Abstract: The TOPGRAD tutorial provides advice on publishing, grant writing and career trajectories in the MICCAI field. The tutorial will consist of a number of talks and discussion on the review process, publishing strategies (including open access) and grant writing requirements. Moreover, we hold an extensive Q&A session between early career researchers and experts in the relevant fields.

Join Dr. Rachel Clipp, Technical Leader, and Aaron Bray, Staff R&D Engineer, from Kitware’s Medical Computing Team on October 9 at the Defense TechConnect Summit.

Poster Session
Wednesday, October 9, from 3:00 to 4:00 p.m. ET

Overview of the Pulse Physiology Engine and its use in Medical Training and Simulation

In this free webinar, Dave DeMarle will provide an overview of Kitware’s Visualization Toolkit. Learn about the origin of VTK, its diverse developer pool and understand its core capability – analyzing 3-dimensional scientific data sets. Don’t miss this opportunity to learn about this state-of-the-art open source software toolkit and ask Dave, one of our Kitware experts, your questions about VTK. Please register here.

Date: October 7, 2019

Time: 11:00 a.m. EDT

Length: 20 mins

Dr. Ken Martin and Cory Quammen will speak about ParaView, Kitware’s open-source, multi-platform data analysis and visualization application that runs on everything from laptops to supercomputers.

Kitware will be presenting 7 courses over four days in July (22-25) at our new Albany NY Headquarters.

Monday July 22

Morning: Introduction to 3D Web visualization

Modern development is pushing applications to run inside Web environments. This course will introduce vtk.js and ParaViewWeb, and explain how these tools enable 3D Visualization inside your web browser.

Afternoon: Managing your data with Girder

Girder is a free and open source web-based data management platform. This course will provide an overview of Girder, including various use cases and extensibility for end-to-end data management, analytics, and visualization.

Tuesday July 23

All Day: CMake and Friends

CMake is open-source software for managing the build and test process of software using compiler-independent methods. This course will teach users the fundamentals of CMake and CTest through a mix of lectures and hands on tutorials.

Wednesday July 24

Morning: Introductory and applied VTK

At this introductory course, attendees learn the fundamental concepts that all users and developers need to know to work with The Visualization Toolkit. A curated selection of hands on exercises, in either C++ or Python, give students first hand experience with VTK’s fundamentals: data structures, data processing and rendering, and user interaction. The course material is annotated with recommended resources for further learning.

Afternoon: Tomviz: Tomography Data from Acquisition to Analysis and Visualization

The course will introduce you to the Tomviz desktop application (Windows, macOS, and Linux binaries available) with a focus on materials tomography data. We will cover the complete pipeline from data acquisition on a TEM microscope to projection image alignment and reconstruction. The more general analysis and visualization of reconstructed tomography data will be covered, along with exporting movies, web scenes, and data. Some advanced topics to be covered include running the pipeline in Docker and adding custom Python-based operators.

Thursday July 25

Morning: A hands on introduction to ParaView

Paraview is an open-source, parallel visualization and analysis application. In this course we provide a hands-on introduction to the ParaView interface, learn how to query the data, work on examples that use common visualization and data analysis filters, describe how to create animations, and how to save a visualization pipeline as a Python script that can be modified and run in batch mode.

Afternoon: Introduction to Computational Model Builder (CMB)

This course will introduce you to the fundamental concepts of Simulation Model ToolKit (SMTK) with examples in both C++ and Python as well as hands on experience with using the Computational Model Builder (CMB) ModelBuilder Application. These combine to manage the core resources and associated operations which are required to define a simulation. Resources include geometric models, simulation information, and meshes.
This course cover use cases from a large range of problem domains, a discussion on how CMB can be applied to your workflow and problem domains, and future enhancements to both SMTK and CMB.

To reserve a seat for the courses, please fill out this google form and we’ll get back to you to confirm you reservation.

https://forms.gle/4Lze8vXrZSyvxWVm6

Kitware at CVPR 2017

Kitware will continue their active participation and support to the computer vision community within this year’s IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). The computer vision team has had a long-term commitment to CVPR and this year will be no different. We will discuss our extensive experience in utilizing deep learning and computer vision to develop tools for image and video scene recognition, object detection and tracking, and image enhancement in talks at multiple workshops.  Domains will include aerial video, ground-level video, underwater video and satellite imagery.  Throughout CVPR 2019, the vision team will continue their high-level of participation as silver sponsors, area chair, reviewers, workshop organizers, speakers, and more. Come by our booth (#1118) to share and discuss Kitware’s computer vision and deep learning techniques supporting the open source software community. Be sure to check out the full details below so you don’t miss this great opportunity to meet with our team.

Event Details:

Kitware is a silver sponsor at this year’s CVPR.  Each year, Kitware sponsors this conference to support this community, recruit computer vision professionals, and to continue collaboration and engagement.  Anthony Hoogs, Ph.D., the Senior Director of Computer Vision, is an Area Chair providing his extensive expertise in computer vision and deep learning to ensure selection of the highest quality papers.

Learning to Explain Artificial Intelligence (AI)

Sunday, June 16 will kick-off the beginning of Kitware’s participation starting with the CVPR-19 Workshop on Explainable Artificial Intelligence (AI).  This workshop “aims to bring together researchers, engineers and industrial practitioners” to discuss relevant topics and concerns related to “interpretability, safety, and reliability of AI”.  Dr. Anthony Hoogs will present detailed information on our accepted paper “Explainability for Content-Based Image Retrieval”. This will be based on our experience performing research and development (R&D) for funded research programs focused on explaining AI. It will be a half-day event located at the Hyatt, Beacon, A; however please check the agenda to ensure no locations have changed at the start of the conference.

Monday June 17, Dr. Anthony Hoogs, the General Co-Chair and organizer of the CVPR 2019 Workshop and Challenge on Automated Analysis of Marine Video for Environmental Monitoring will begin.  This full-day workshop includes“experts and researchers interested in learning about the challenges, current work, and opportunities in marine video analytics, including video captured from both under and above water”. Monitoring fish, shellfish, marine mammals, coral reefs, bottom habitats, and other wildlife continues to be of great interest to oceanographers, biologists, and others.  Maritime video collection is expanding exponentially as professionals work to determine new ways to use this data for marine science and oceanography. The challenges in this environment are vast and many experts and researchers are diligently working to overcome these challenges to enable increased automated video processing. Currently, marine video is annotated manually, resulting in a tremendous bottleneck to studying marine biological problems such as fish population estimates. Under NOAA funding, Kitware has developed an open-source framework and toolkit, Video and Imagery Analytics for the Marine Environment (VIAME), to integrate analytics algorithms from the community into an operational capability for NOAA.

Video and Imagery Analytics for the Marine Environment (VIAME) Toolkit

This Workshop will feature a data challenge within this domain, in addition to the invited talks and selected papers.  Large amounts of image data from a variety of underwater cameras and environments has been provided and annotated by the National Oceanic and Atmospheric Administration (NOAA). Challenge entries must work towards achieving the highest detection and classification accuracy of organisms in the provided videos. Results will be scored and ranked by Kitware, and the top three entries will present their solutions at the workshop.  Check out the Challenge website for more information.

Textured 3D Mesh of Jacksonville

Kitware will also be presenting and participating in the EARTHVISION 2019 IEEE/ISPRS Workshop June 17.  The need for automated interpretation of remotely sensed data is always present to positively support human society, economy, industry, and the planet.  It is evolving and highly challenging, therefore awareness within the computer vision community needs to be raised to support and develop tools to improve data mining, multi-sensor, multi-modality, multi-temporal, and multi-resolution fusion and more. This workshop focuses on large scale computer vision for remote sensing in imagery and is a full-day event with invited talks, poster spotlights and presentations.  This year, Kitware was awarded the “Best Paper Presentation” for this workshop titled “Urban Semantic 3D Reconstruction from Multiview Satellite Imagery”.  Matt Leotta, Ph.D., a Technical Lead within Kitware’s Computer Vision team, will be presenting this research to the community; with additional Kitware attendees and authors, such as Chengjiang Long, Ph.D., a Computer Vision Researcher with Kitware.

The Workshop on Media Forensics will also be held on Monday, June 17.  This workshop will discuss topics such as media forensics, reconstruction of media genealogy, analysis and detection of imagery and videos created by new synthesis methods such as Generative Adversarial Networks (GANs) and more. Kitware’s, Dr. Chengjiang Long will  present a spotlight presentation starting at 9:30 am PST on the paper titled “A Coarse-to-fine Deep Convolutional Neural Network Framework for Frame Duplication Detection and Localization in Forged Videos”. It proposes a novel coarse-to-fine framework based on deep Convolutional Neural Networks to automatically detect and localize frame duplication.  In addition to this, keynote speakers for universities and government organizations will discuss research, challenges and real-world needs based on media forensics now. Make sure to come check out this workshop in room 102A and the others at CVPR 2019!

Finally, during the main conference and exhibition, Kitware’s computer vision team members including Anthony Hoogs, Ph.D.,  Keith Fieldhouse, Matt Leotta, Ph.D., Brian Clipp, Ph.D., Matt Dawkins, Chengjiang Long, Ph.D., Heather James, and John Westbrook will be available at booth #1118 to discuss and demonstrate Kitware’s computer vision expertise.  You will have the opportunity to see the KitWare Image and Video Exploitation and Retrieval (KWIVER) toolkit, Kitware’s open source software toolkit that contains advanced computer vision tools to perform object detection and tracking; activity, event, and threat detection; scene understanding; and social multimedia analysis.  In addition, our work on the Video and Image Analytics for a Marine Environment (VIAME) toolkit will be demonstrated as we are continuously working with NOAA to develop open source software for fish monitoring and extending that to other capabilities and needs.

About Kitware’s Computer Vision Team:

Kitware’s Computer Vision team recognizes how valuable advancing computer vision and deep learning is in order to greatly improve and push capabilities beyond their limits supporting Academia, Industry, and the DoD and Intelligence Communities.  Our main focus areas include deep learning, object detection and tracking, image and video scene understand, image and video forensics, social multimedia analysis, complex activity, event, and threat detection, 3D vision, and super resolution; however we are not limited and continuously explore and participate in other research and development for our customers and our partners.  We partner with many academic institutions such as Harvard, Massachusetts Institute of Technology, Cornell University, University of California, Berkeley, and Texas A&M University. We have worked with various agencies, such as the Defense Advanced Research Project Agency (DARPA), Air Force Research Laboratory (AFRL), the Office of Naval Research (ONR), Intelligence Advanced Research Projects Activity (IARPA) and the U.S. Air Force.  Kitware has developed and deployed an operational Wide Area Motion Imagery (WAMI) tracking systems for Intelligence, Surveillance, and Reconnaissance (ISR) in theatre, providing analysts with exploitation capabilities that fuse sensors, platforms, and people. Our work with DARPA on Squad-X has led to extensive research, development, and deployment of robust methods to more accurately identify and track objects and people, delivered straight to the soldier on the ground.  Our work on the Visual Global Intelligence and Analytics Toolkit (VIGILANT), funded by the Air Force Research Laboratory (AFRL) via the Small Business Innovation Research (SBIR) program is a collaborative effort with Rochester Institute of Technology’s (RIT’s) Digital Imaging and Remote Sensing (DIRS) and Real Time Vision and Image Processing (RTVIP) Labs and the Middlebury Institute of International Studies at Monterey, James Martin Center for Nonproliferation Studies to develop object and object-based change detection and unstructured change detection in satellite imagery. In addition, Kitware is continually improving their KitWare Image and Video Exploitation and Retrieval (KWIVER) toolkit, which is an open source framework for video and image analytics built from Kitware’s years of experience developing analytic systems for various customers in multiple domains.  Please visit our computer vision and KWIVER webpages for more information into our key focus areas and experience.

Contact:

Please reach out to computervision@kitware.com to schedule meetings throughout this event.  We are looking forward to engaging with this community and sharing information on Kitware’s ongoing research and capability development in computer vision and deep learning as well as our cutting-edge open source vision software, KWIVER and VIAME.

The United States Geospatial Intelligence Foundation (USGIF) GEOINT 2019 Symposium is just around the corner!  This is Kitware’s first year to have a booth at GEOINT and we are very excited.  Come visit us at booth #1430 to learn more about our advanced computer vision capabilities and how they translate to geospatial intelligence.

Are you interested in machine learning in satellite and marine imagery?  We are holding a training session titled “Interactive Machine Learning in Satellite and Marine Imagery”.  This training session will demonstrate interactive and machine learning (ML) by analysts based on the open-source Visual Global Intelligence and Analytics Toolkit (VIGILANT) and Video and Image Analytics for Marine Environments (VIAME) systems.  These systems allow analysts to develop ML-based object detectors without the need for any programming, all within minutes.  Check out our teaser video below and we look forward to seeing you on Monday June 3 in room 302A from 2-4 pm.

Over the years, Kitware has continuously developed exciting and forward thinking technologies that support the GEOINT community.  This is all through the use of our specialized team and computer vision and deep learning techniques.  These techniques help Kitware build advanced tools and capabilities to support intelligence operations through threat detection and more.  By adopting and harnessing deep learning techniques tied with computer vision, Kitware has demonstrated dramatic improvements in technologies.  Our focus is on hard problems such as extracting meaningful information from low resolution images and video and/or small training sets.  In addition, we scale these technologies to handle large data volumes associated with object detection and tracking, event and activity recognition, scene understanding, 3D vision, threat detection, and more.

Contact:

This year we will have members of the computer vision team attending sessions and at the booth.  Please reach out at computervision@kitware.com or 202-725-9389 to schedule meetings throughout GEOINT 2019.  We look forward to speaking with you about Kitware’s technologies, solutions, and your challenges!

NVIDIA and Kitware have teamed up to provide a free one-hour webinar on using GPU-accelerated ray tracing in ParaView and VTK to improve understanding of your scientific visualizations.

Highlights include:

• How to use OptiX Ray Tracer inside ParaView
• Leverage simulations with ParaView
• How ray tracing can provide more insights into data

Click here to register

Beatriz Paniagua, Ph.D., a technical leader on the medical team at Kitware, will join a roundtable forum to determine cross-discipline interests between the biomedical and radio astronomical imaging research communities.

More information can be found at the forum’s website.