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In this paper we consider the problem of describing the action being performed by human figures in still images. We will attack this problem using an unsupervised learning approach, attempting to discover the set of action classes present in a large collection of training images. These action classes will then be used to label test images. Our approach uses(More)
We present a novel convex programming scheme to solve matching problems, focusing on the challenging problem of matching in a large search range and with cluttered background. Matching is formulated as metric labeling with L<sub>1</sub> regularization terms, for which we propose a novel linear programming relaxation method and an efficient successive(More)
Abstract Several color object recognition methods that are based on image retrieval algorithms attempt to discount changes of illumination in order to increase performance when test image illumination conditions differ from those that obtained when the image database was created. Here we extend the seminal method of Swain and Ballard to discount changing(More)
Data Mining is a young but ourishing eld. Many algorithms and applications exist to mine di erent types of data and extract di erent types of knowledge. Mining multimedia data is, however, at an experimental stage. We have implemented a prototype for mining high-level multimedia information and knowledge from large multimedia databases. MultiMediaMiner has(More)
We propose human action detection based on a successive convex matching scheme. Human actions are represented as sequences of postures and specific actions are detected in video by matching the time-coupled posture sequences to video frames. The template sequence to video registration is formulated as an optimal matching problem. Instead of directly solving(More)
With huge amounts of multimedia information connected to the global information network (Internet), e cient and e ective image retrieval from large image and video repositories has become an imminent research issue. This article presents our research in the C-BIRD (Content-Based Image Retrieval in Digital-libraries) project. In addition to the use of common(More)
With huge amounts of multimedia information connected to the global information network (Internet), efficient and effective image retrieval from large image and video repositories has become an imminent research issue. This article presents our research in the C-BIRD (Content-Based Image Retrieval from Digital libraries) project. In addition to the use of(More)
Multimedia data mining is the mining of high-level multimedia information and knowledge from large multimedia databases. A multimedia data mining system prototype, MultiMediaMiner, has been designed and developed. It includes the construction of a multimedia data cube which facilitates multiple dimensional analysis of multimedia data, primarily based on(More)
Image-based rendering takes as input multiple images of an object and generates photorealistic images from novel viewpoints. This approach avoids explicitly modeling scenes by replacing the modeling phase with an object reconstruction phase. Reconstruction is achieved in two possible ways: recovering 3D point locations using multiview stereo techniques, or(More)