Title :
A spatiotemporal tensor-based multi-object matching algorithm
Author :
Cheng, Jun ; Xie, Qi ; Li, Pengcheng ; Yuan, Ruifeng
Author_Institution :
Shenzhen Institutes of Adv. Technol., Chinese Acad. of Sci., Shenzhen, China
Abstract :
A multi-object matching algorithm based on spatiotemporal tensor is proposed for stereo localization systems with binocular views. Multi-object matching is formulated as a graph matching problem, which forms an efficient and extensible framework for the various matching cases. Then, the spatiotemporal tensor, including appearance, geometric and temporal cues, is used to improve the reliability and accuracy rate of matching in various conditions. Also, a high-order graph matching algorithm is introduced and improved. The experimental evaluation shows that proposed algorithm is robust to various cases, accurate in terms of matching rate, while being time-consuming little.
Keywords :
graph theory; image matching; stereo image processing; binocular views; geometric cues; graph matching problem; multiobject matching algorithm; spatiotemporal tensor; stereo localization systems; temporal cues; Classification algorithms; Tracking; Multi-Object; graph matching; tensor-based;
Conference_Titel :
Information Networking and Automation (ICINA), 2010 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-8104-0
Electronic_ISBN :
978-1-4244-8106-4
DOI :
10.1109/ICINA.2010.5636378