Detection and Tracking of Humans and Faces. (21st February 2008)

• Record Type: Journal Article
• Authors: Karlsson, Stefan; Taj, Murtaza; Cavallaro, Andrea
• Other Names: Pantic Maja Academic Editor.
• Is Part Of: EURASIP journal on image and video processing. Volume 2008(2008)
• Publication Date: 2008-02-21
• Subjects: Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; Traitement d'images; Vidéo numérique; Digital video; Image processing -- Digital techniques; Periodicals; Electronic journal; Electronic journals; 621.367
• DOI: 10.1155/2008/526191
• Languages: English
• ISSNs: 1687-5176

Abstract

Abstract : We present a video analysis framework that integrates prior knowledge in object tracking to automatically detect humans and faces, and can be used to generate abstract representations of video (key-objects and object trajectories). The analysis framework is based on the fusion of external knowledge, incorporated in a person and in a face classifier, and low-level features, clustered using temporal and spatial segmentation. Low-level features, namely, color and motion, are used as a reliability measure for the classification. The results of the classification are then integrated into a multitarget tracker based on a particle filter that uses color histograms and a zero-order motion model. The tracker uses efficient initialization and termination rules and updates the object model over time. We evaluate the proposed framework on standard datasets in terms of precision and accuracy of the detection and tracking results, and demonstrate the benefits of the integration of prior knowledge in the tracking process.