DocumentCode
3116162
Title
A Novel Algorithm for Moving Objects Recognition Based on Sparse Bayesian Classification
Author
Changhua, Lu ; Ningning, Chang ; Rui, Fang ; Chun, Liu
Author_Institution
Sch. of Comput. & Inf., Hefei Univ. of Technol., Hefei
fYear
2006
fDate
6-8 Sept. 2006
Firstpage
135
Lastpage
139
Abstract
This paper deals with the problem of moving objects recognition using Bayesian method. A novel algorithm based on sparse Bayesian classification for the recognition of moving objects is proposed. This approach takes full advantage of sparse Bayesian in solving classification problems. It uses fewer kernel functions in order to reduce the complexity of the computation and resolves the over-fitting problem in recognition system. The experimental results show that this approach distinctly outperforms other classification approaches on this issue. The veracity and velocity are also satisfactory.
Keywords
Bayes methods; computational complexity; image classification; image motion analysis; object recognition; computation complexity reduction; kernel function; moving object recognition; sparse Bayesian classification; Automatic control; Bayesian methods; Control systems; Feature extraction; Image recognition; Kernel; Lighting; Object recognition; Support vector machine classification; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning for Signal Processing, 2006. Proceedings of the 2006 16th IEEE Signal Processing Society Workshop on
Conference_Location
Arlington, VA
ISSN
1551-2541
Print_ISBN
1-4244-0656-0
Electronic_ISBN
1551-2541
Type
conf
DOI
10.1109/MLSP.2006.275536
Filename
4053635
Link To Document