This paper shows how the output of a number of detection and tracking algorithms can be fused to achieve robust tracking of people in an indoor environment. The new tracking system...
We propose statistical data association techniques for visual tracking of enormously large numbers of objects. We do not assume any prior knowledge about the numbers involved, and...
Margrit Betke, Diane E. Hirsh, Angshuman Bagchi, N...
Conventional level set based approaches have an inherent difficulty in tracking miscible fluids due to its discrete treatment for interface. This paper proposes a unified framewor...
Jinho Park, Younghui Kim, Daehyeon Wi, Nahyup Kang...
The varying object appearance and unlabeled data from new frames are always the challenging problem in object tracking. Recently machine learning methods are widely applied to tra...
As environments become smart in accordance with advances in ubiquitous computing technology, researchers are struggling to satisfy users' diverse and sophisticated demands. Th...
Jin Choi, Yong-il Cho, Kyusung Cho, Su-jung Bae, H...