Paper Info
Title
A rule-based method for object segmentation in video sequences
Abstract
Object segmentation and tracking are problems within the scope of MPEG-4 and MPEG-7 standardization activities. A novel algorithm for both object segmentation and tracking is presented. The algorithm fuses motion, color, and accumulated previous segmentation data at `region level', in contrast to conventional `pixel level' approaches. The information fusion is achieved by a rule-based region processing unit which intelligently utilizes the motion information to locate the objects in the scene, the color information to extract the true boundaries, and the segmentation result of the previous frame for tracking the objects. The algorithm is generic in the sense that the modules prior to the rule-based region processor can independently be replaced by alternative units which can achieve the same tasks. In the proposed algorithm, while the recursive-shortest-spanning-tree (RSST) algorithm is used for segmentation purposes, hierarchical-block-matching (HBM) is utilized for estimating motion between frames. The simulation results are very promising for this novel object segmentation approach
Year
DOI
Venue
1997
10.1109/ICIP.1997.638823
ICIP (2)
Keywords
Field
DocType
recursive-shortest-spanning-tree algorithm,video signal processing,knowledge based systems,hierarchical-block-matching,image matching,motion information,video sequences,mpeg-7,region level,trees (mathematics),rule-based region processing unit,information fusion,rsst algorithm,image segmentation,true boundaries,hbm,color,object segmentation,frame,motion estimation,rule-based method,optical tracking,edge detection,tracking,standardization,image sequences,object detection,accumulated previous segmentation data,mpeg-4,sensor fusion,image colour analysis,rule based,fuses,layout,data mining,mpeg 4
Object detection,Computer vision,Rule-based system,Scale-space segmentation,Pattern recognition,Computer science,Segmentation,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Region growing,Motion estimation
Conference
Volume
ISBN
Citations 
2
0-8186-8183-7
8
PageRank 
References 
Authors
0.93
2
3
Name
Order
Citations
PageRank
A. Aydin Alatan165585.78
Ertem Tuncel238636.48
Levent Onural311016.83