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: Automatic Video Object Segmentation Using Volume Growing and Hierarchical Clustering | EURASIP Journal on Applied Signal Processing 2004 6 814-832 2004 Hindawi Publishing Corporation Automatic Video Object Segmentation Using Volume Growing and Hierarchical Clustering Fatih Porikli Mitsubishi Electric Research Laboratories Cambridge MA 02139 USA Em ail fatih@ Yao Wang Department of Electrical Engineering Polytechnic University Brooklyn NY 11201 USA Email yao@ Received 4 February 2003 Revised 26 December 2003 We introduce an automatic segmentation framework that blends the advantages of color- texture- shape- and motion-based segmentation methods in a computationally feasible way. A spatiotemporal data structure is first constructed for each group of video frames in which each pixel is assigned a feature vector based on low-level visual information. Then the smallest homogeneous components so-called volumes are expanded from selected marker points using an adaptive three-dimensional centroid-linkage method. Self descriptors that characterize each volume and relational descriptors that capture the mutual properties between pairs of volumes are determined by evaluating the boundary trajectory and motion of the volumes. These descriptors are used to measure the similarity between volumes based on which volumes are further grouped into objects. A fine-to-coarse clustering algorithm yields a multiresolution object tree representation as an output of the segmentation. Keywords and phrases video segmentation object detection centroid linkage color similarity. 1. INTRODUCTION Object segmentation is important for video compression standards as well as recognition event analysis understanding and video manipulation. By object we refer to a collection of image regions grouped under some homogeneity criteria where a region is defined as a contiguous set of pixels. Basically segmentation techniques can be grouped into three classes region-based methods using a homogeneous color or texture criterion motion-based approaches utilizing a .
