Automatic Video-based Motion Analysis

Operations in confined, isolated, and resource-constrained environments can lead to suboptimal human performance. Understanding task performance and crew behavioral health is crucial to mission success and the optimal design, development and operation of next generation space craft. Onboard resources, such as a single conventional video camera, can capture crew motion and interaction. There is a critical need for a software tool which achieves unobtrusive, non-invasive, automatic analysis of crew activity from video footage. Many video-based human motion analysis tools assume a stationary camera and employ segmentation techniques like temporal differencing or background segmentation to detect people. However, these approaches are vulnerable to camera motion and subtle changes in the background. In addition, many existing commercial solutions use simple blob-based video analysis where the entire body is tracked as a single object. Employing such a coarse human body model is appropriate for surveillance applications concerned with motion detection and person counting; however, it is insufficient for understanding precise human actions or gestures. Therefore, a system which is able to detect human body pose automatically, regardless of camera setup, is necessary for addressing these issues. Vecna proposes a video analysis software tool that automatically processes and analyzes complex human motions in conventional 2D video without the use of specialized markers. Unlike many video analytics solutions, Vecna's solution goes beyond simple blob-based video analysis by tracking the geometric configuration of human body parts like the trunk, head, and limbs. This enables our human motion understanding algorithms to model and recognize complex human actions and interactions. The resulting system will represent a substantial breakthrough providing benefits to an array of applications in video surveillance, human-computer interaction, human factors engineering, and robotics.

Vecna expects the full-scope software system to have immediate and tangible benefit for NASA's Exploration Systems Mission Directorate (ESMD). ESMD focuses on the human element of exploration by conducting research to ensure astronaut explorers are safe, healthy and can perform their work during long-duration space exploration. Task performance and crew behavioral health are key concerns in the design, development, and operation of next generation space vehicles. Operations in confined, isolated, and resource-constrained environments can lead to suboptimal human performance. As such, there is a critical need for Vecna's proposed software tool that automatically processes and analyzes crew motion and interaction from video footage captured by a single conventional 2D video camera. Such a diagnostic tool will enable unobtrusive and non-invasive measurement of task performance and crew behavioral health.

The proposed technology is applicable to a wide range of Department of Defense and intelligence community areas including force protection, counter-terrorism, target recognition, human activity monitoring, and surveillance and tracking. We see significant potential for application of this tool to support a range of tactical and strategic systems, including shipboard Navy CIC centers, Army field C3I centers, or USAF theater airborne command posts. A number of programs sponsored by the Department of Defense (e.g. FCS, HumanID, CTS, Mind's Eye, Rail Security Pilot) employ video-based monitoring systems and would benefit from the proposed system. In addition, Vecna will investigate commercialization opportunities in a variety of sectors, including mobile robotics and visual surveillance. Initial analysis of these market segments reveal both unaddressed needs as well as vast potential for rapid adoption and growth. As robotic systems become more commonplace in today's society, robust, intelligent interaction between humans and robots is essential. Interaction with humans in a lifelike manner requires that robot infer physical intentions by interpreting visual cues. The proposed technology could potentially revolutionize human-robot interaction. In the surveillance market, an immediate application is automated screening of passengers and personnel at busy transportation hubs such as airline terminals and ports, and 24/7 automation of border monitoring and control.

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