Army Subcontract for Scene Change Analysis in Video from Mobile Camera: 10.15.2008
Prof. Shah has been awarded a subcontract from the Army Research Labs for his proposal title "Video-Based Change Detection". Research performed under this subcontract will address the problem of automated detection of regions of change in video sequences of the same scene taken at different times. Solution to this problem is crucial in vision tasks, especially in various applications related to video surveillance, remote sensing, medical diagnosis and treatment, and driver assistance systems.
Texas Norman Hackerman Advanced Research Program award for Distributed Surveillance: 05.05.2008
Prof. Kakadiaris, Eckhard Pfeiffer Professor, and Prof. Shah, Assistant Professor, in collaboration with Prof. Jejelowo (Texas Southern University) received an ARP award of $149,944 for two years for their proposal "Video-Based Surveillance in Distributed Environments".
DURIP award for collaborative computer vision research: 05.01.2008
A Defense University Research Instrumentation Program (DURIP) grant from the Army Research Office has been recently awarded to a team of UH researchers led by the Principal Investigator Prof. Shishir Shah, Assistant Professor of Computer Science. Co-PIs for this award are Assistant Professors Edgar Gabriel and Rong Zheng and Professor Marc Garbey. The $140,000 award will be used to purchase mobile robots with vision capabilities, static cameras, compute nodes, and storage servers for processing, analyzing, storing and retrieving the data streams produced by multiple cameras, and wireless communication devices for video transmission and monitoring.
The automated interpretation of images to detect, track, recognize, and understand the trajectories of objects in a timely manner is crucial in vision tasks, especially in various activities of the Department of Defense, including automatic target detection and recognition (ATD/R), surveillance and monitoring, autonomous navigation for smart weapons, and industrial robotics for manufacturing and deployment of weapon systems, among others. Within a realistic environment, scene understanding and imaging of objects is a distributed act that requires interpretation of the image data based on a highly scalable and collaborative mechanism.
The equipment purchased through this award will be utilized to further research efforts in the area of distributed and high performance mobile multi-modal smart camera system for scene sensing and vision tasks related to object detection, tracking, and recognition. Research enabled by this award will be the key enabler to real-time monitoring of the environment and information processing needed for mission critical assessment of friend/foe targets.
“We expect the equipment purchased through this award to be a pivotal capability for distributed and high performance vision research in at least five areas: evidence-based object recognition, multi-modality disparate view-based object recognition, spatial pattern analysis and wide-area monitoring, real-time resource allocation and distributed computing, and quality-of-service aware wireless communication”, said Prof. Shah.
The award is one of 210 DURIP awards announced by the Department of Defense in March 2008 and the first ever to be awarded to the University of Houston. DURIP awards support the purchase of state-of-the-art equipment that augments current capabilities or develops new university capabilities to perform cutting-edge defense research. They enable DoD-supported university researchers to purchase scientific equipment costing $50,000 or more.
Invited Lecture at The University of Texas at Austin: 03.30.2008
Dr. Shah was invited to give a talk at The University of Texas at Austin as part of the ECE Seminar Series. He presented results of his recent work in the area of Learning Systems in Computer Vision and discussed future directions. Abstract of his talk can be seen at ECE Seminar Series page.
Spring 2008 Course Offering: 12.03.2007
COSC 6343 Pattern Recognition will be offered in Spring 2008. For details please see the course website.