Tackle challenging image and video analysis problems with KWIVER
Kitware offers advanced R&D services in support of KWIVER. Find out how we can help develop an end-to-end solution for your challenges in automated image and video analysis.
The Kitware Image and Video Exploitation and Retrieval (KWIVER) toolkit is a collection of software tools designed to tackle challenging image and video analysis problems and other related challenges. Recently started by Kitware’s Computer Vision and Scientific Visualization teams, KWIVER is an ongoing effort to transition technology developed over multiple years to the open source domain to further research, collaboration, and product development.
Existing KWIVER Open Source Repositories
KWIVER: KWIVER is the parent repository of the rest of the KWIVER system. It is a CMake “super-build” that pulls together the other elements of the KWIVER project and provides configuration and integration that help you use KWIVER to build your own exploitation systems. This is where you should start.
Motion-imagery Aerial Photogrammetry Toolkit (MAP-TK) : MAP-TK is an open source C++ collection of libraries and tools for making measurements from aerial video. Initial capability focuses on estimating the camera flight trajectory and a sparse 3D point cloud of the scene.
Super3D : Super3D is an experimental codebase that addresses the problems of image super resolution and dense 3D depth estimation using multiple images from differing viewpoints.
Social Multimedia Query Toolkit (SMQTK) : A collection of Python tools, with C++ dependencies, for ingesting images and video from social media (e.g. YouTube, Twitter), computing content-based features, indexing the media based on the content descriptors, querying for similar content, and building user-defined searches via an interactive query refinement (IQR) process.
Stream Processing Toolkit (sprokit) : Sprokit is the “Stream Processing Toolkit”, a library aiming to make processing a stream of data with various algorithms easy. It supports divergent and convergent data flows with synchronization between them, connection type checking, all with full, first-class Python bindings.
VisCL : VisCL is an experimental codebase that explores OpenCL for visual feature detection and tracking acceleration. OpenCL is an open standard designed for cross-platform parallel execution on GPUs, CPUs, and other hardware.
VIVIA : A collection of Qt based applications for GUIs, visualization and exploration of content extracted from video.
Fletch : A CMake based project that assists with acquiring and building common Open Source libraries useful for developing video exploitation tools.
Video and Image-Based Retrieval and Analysis Toolkit (VIBRANT) : An end-to-end system for surveillance video analytics including content-based retrieval and alerting using behaviors, actions and appearance.
KWant : A lightweight toolkit for computing detection and tracking metrics on a variety of video data. It computes spatial and temporal associations between datasets, even with different frame rates. It has a flexible input format and can generate XML based results.
Existing KWIVER Government Open Source Repositories (on Forge.mil)
Kitware’s WAMI Tracker (Requires Forge.mil account) : The product of multiple years of development, Kitware’s real-time, full-frame WAMI tracker has been used operationally overseas. The tracker is available as source code for government use on forge.mil. A forge.mil account is required for access and is available with government sponsorship.
Existing Data Sets
VIRAT video dataset : The VIRAT video dataset contains more than ten hours of realistic, natural, and challenging video surveillance data, particularly in terms of its resolution, background clutter, diversity in scenes, and human activity/event categories. Ground truth is provided for all movers and more than 10 event types.
Planned Public Open Source Repositories & Data Sets
Kitware is working toward making the following repositories and data sets available:
- WorkQL : A PostgreSQL based synchronization library for developing distributed, pipeline- oriented, data processing systems.