tailieunhanh - Báo cáo hóa học: " Research Article Track and Cut: Simultaneous Tracking and Segmentation of Multiple Objects with Graph Cuts"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Track and Cut: Simultaneous Tracking and Segmentation of Multiple Objects with Graph Cuts | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2008 Article ID 317278 14 pages doi 2008 317278 Research Article Track and Cut Simultaneous Tracking and Segmentation of Multiple Objects with Graph Cuts Aurelie Bugeau and Patrick Perez Centre Rennes-Bretagne Atlantique INRIA Campus de Beaulieu 35 042 Rennes Cedex France Correspondence should be addressed to Aurelie Bugeau Received 24 October 2007 Revised 26 March 2008 Accepted 14 May 2008 Recommended by Andrea Cavallaro This paper presents a new method to both track and segment multiple objects in videos using min-cut max-flow optimizations. We introduce objective functions that combine low-level pixel wise measures color motion high-level observations obtained via an independent detection module motion prediction and contrast-sensitive contextual regularization. One novelty is that external observations are used without adding any association step. The observations are image regions pixel sets that can be provided by any kind of detector. The minimization of appropriate cost functions simultaneously allows detection-before-track tracking track-to-observation assignment and automatic initialization of new tracks and segmentation of tracked objects. When several tracked objects get mixed up by the detection module . a single foreground detection mask is obtained for several objects close to each other a second stage of minimization allows the proper tracking and segmentation of these individual entities despite the confusion of the external detection module. Copyright 2008 A. Bugeau and P. Perez. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION Visual tracking is an important and challenging problem in computer vision. Depending on applicative context under concern it .