Contextual information is vital for the robust extraction of semantic information in automated surveillance systems. We have developed a scene independent framework for the detect...
In this paper, we focus on the use of context-aware, collaborative filtering, machine-learning techniques that leverage automatically sensed and inferred contextual metadata toget...
Marc Davis, Michael Smith, John F. Canny, Nathan G...
This paper proposes a novel approach to extract meaningful content information from video by collaborative integration of imageunderstanding and natural language processing. As an...
In this paper we present an evaluation method for stereo matching systems and sensors especially for real world indoor applications. We estimate ground truth reference images by i...
Martin Humenberger, Daniel Hartermann, Wilfried Ku...
This paper aims at discovering community structure in rich media social networks, through analysis of time-varying, multi-relational data. Community structure represents the laten...
Yu-Ru Lin, Jimeng Sun, Paul Castro, Ravi B. Konuru...