DocumentCode
2394262
Title
A method of type recognition using probabilistic constraint support vector machine
Author
Jie, Man
Author_Institution
Eng. Training, Yantai Univ., Yantai, China
fYear
2012
fDate
19-20 May 2012
Firstpage
1796
Lastpage
1799
Abstract
A new support vector machine classifier for recognition of vehicle type which has been captured from traffic scene images. A new support vector machine classifier is presented with probabilistic constrains which presence probability of samples in each class is determined based on a distribution function. Noise is caused to found incorrect support vectors thereupon margin can not be maximized. In the proposed method, constraints boundaries and constraints occurrence have probability density functions which it helps for achieving maximum margin.
Keywords
image recognition; probability; support vector machines; traffic engineering computing; vehicles; SVM classifier; constraints boundaries; constraints occurrence; distribution function; maximum margin; probabilistic constraint support vector machine; probability density functions; traffic scene images; vehiche type recognition; Feature extraction; Optimization; Pattern recognition; Probabilistic logic; Reliability; Support vector machines; Vehicles; Machine identification; Pattern recognition; Probabilistic constraints; Support vector machine; Vehicle type recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems and Informatics (ICSAI), 2012 International Conference on
Conference_Location
Yantai
Print_ISBN
978-1-4673-0198-5
Type
conf
DOI
10.1109/ICSAI.2012.6223393
Filename
6223393
Link To Document