This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
In this paper, we present the results of a project that seeks to transform low-level features to a higher level of meaning. This project concerns a technique, latent semantic anal...
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...
We present a new visualization method for 2d flows which allows us to combine multiple data values in an image for simultaneous viewing. We utilize concepts from oil painting, art...
In the current video analysis scenario, effective clustering of shots facilitates the access to the content and helps in understanding the associated semantics. This paper introdu...