TY - GEN
T1 - Simultaneous object tracking and classification for traffic surveillance
AU - Tuty, Julfa
AU - Zhang, Bailing
N1 - Funding Information:
The project is supported by Suzhou Municipal Science and Technology Foundation grants SS201109 and SYG201140.
Publisher Copyright:
© Springer India 2014.
PY - 2014
Y1 - 2014
N2 - Object tracking is the problem of estimating the positions of moving objects in image sequences, which is significant in various applications. In traffic surveillance, the tasks of tracking and recognition of moving objects are often inseparable and the accuracy and reliability of a surveillance system can be generally enhanced by integrating them. In this paper, we proposed a traffic surveillance system that features of classification of pedestrian and vehicle types while tracking, which works well in challenging real-word conditions. The object tracking is implemented by the Mean Shift and object classification is implemented with several different classification algorithms including k-nearest neighborhood (kNN), support vector machine (SVM), multi-layer perceptron (MLP), and random forest (RF), with high classification accuracies.
AB - Object tracking is the problem of estimating the positions of moving objects in image sequences, which is significant in various applications. In traffic surveillance, the tasks of tracking and recognition of moving objects are often inseparable and the accuracy and reliability of a surveillance system can be generally enhanced by integrating them. In this paper, we proposed a traffic surveillance system that features of classification of pedestrian and vehicle types while tracking, which works well in challenging real-word conditions. The object tracking is implemented by the Mean Shift and object classification is implemented with several different classification algorithms including k-nearest neighborhood (kNN), support vector machine (SVM), multi-layer perceptron (MLP), and random forest (RF), with high classification accuracies.
KW - Mean shift
KW - Object classification
KW - Object tracking
KW - Traffic surveillance
UR - http://www.scopus.com/inward/record.url?scp=84927537380&partnerID=8YFLogxK
U2 - 10.1007/978-81-322-1759-6_86
DO - 10.1007/978-81-322-1759-6_86
M3 - Conference Proceeding
AN - SCOPUS:84927537380
T3 - Advances in Intelligent Systems and Computing
SP - 749
EP - 755
BT - International Conference on Computer Science and Information Technology, CSAIT 2013, Proceedings
A2 - Patnaik, Srikanta
A2 - Li, Xiaolong
PB - Springer Verlag
T2 - International Conference on Computer Science and Information Technology, CSAIT 2013
Y2 - 21 September 2013 through 23 September 2013
ER -