Automated Person Categorization in Video Using Soft Biometrics Navy SBIR FY2008.1 Sol No.: Navy SBIR FY2008.1 Topic No.: N08-077 Topic Title: Automated Person Categorization in Video Using Soft Biometrics Proposal No.: N081-077-0340 Firm: intuVision 100-F Tower Office Park Woburn, Massachusetts 01801 Contact: Sadiye Guler Phone: (781) 497-1015 Web Site: intuvisiontech.com Abstract: In this proposal, intuVision and partner West Virginia University Biometric Research Group propose to research, design, and develop a feasibility prototype for a Video Tracking and Object Re-Identification (VTORI) system that can support entity re-identification among multiple sensors and databases. Firstly, we will focus on surveillance video data, explore soft biometry features that can be robustly extracted from different types of video sources and reliably used for subsequent analysis and implement these soft biometry features into our team's existing video product test platforms to validate our concept prototype. Secondly, we will create a metadata dictionary and a standard description scheme for soft biometry features to facilitate efficient exchange of extracted identification information between different sensors and systems. Our approach is built on our team's expertise and leverages our previous and current related work in video object tracking, feature extraction for video object classification and camera hand-off of tracked objects and study of face, gait and human metrology based biometric features from video. Benefits: The soft biometrical feature extraction and use of these features in person categorization will be transitioned into existing intuVision video analyis products to benefit the end users. Within this first phase of the project we will develop:  A framework for extracting human metrology, gait and coarse face based soft biometric features from video,  An evaluation method to assess robustness of extracted features for a given video data source,  A metadata representation, storage and exchange scheme for soft biometry features, and  An early prototype implementation of these concepts leveraging existing intuVision rapid R&D platform and application projects to transition the developed technologies. Return