Paper Info
Title
Evolutionary Algorithm-Based Local Structure Modeling for Improved Active Shape Model
Abstract
An evolutionary algorithm-based robust local structure modeling technique is proposed to improve the performance of the active shape model (ASM). The proposed algorithm can extract boundary of an object under adverse condition, such as noisy corruption, occlusions, and shadow effect. The principle idea of the evolutionary algorithm is to find the global minimum of an objective function by evolving from a large set of populations rather than a single solution which may cause a local minimum. The proposed algorithm has been tested for various images including a sequence of human motion to demonstrate the improved performance of object tracking based on the evolutionary ASM.
Year
DOI
Venue
2004
10.1007/978-3-540-24653-4_37
Lecture Notes in Computer Science
Keywords
Field
DocType
evolutionary algorithm,objective function,active shape model,object tracking
Active shape model,Shadow,Evolutionary algorithm,Object-oriented programming,Computer science,Algorithm,Video tracking,Genetic algorithm,Principal component analysis,Abstract machine
Conference
Volume
ISSN
Citations 
3005
0302-9743
0
PageRank 
References 
Authors
0.34
3
6
Name
Order
Citations
PageRank
Jeongho Shin112417.26
Hyunjong Ki211.72
Vivek Maik3394.33
Jinyoung Kang421.42
Junghoon Jung584.67
Joon Ki Paik612918.73