CVL Seminar: "Multi-target Tracking by Rank-1 Tensor Approximation" by Haibin Ling - Temple University

Wed Apr 10, 2013 11:00 AM

Computer Vision Laboratory
Center for Automation Research
A.V. Williams Building, Room 1146

Haibin Ling
Dept. of Computer and Information Sciences
Temple University

Multi-target tracking (MTT) is an important problem in computer vision and has many applications. We introduce a novel framework for MTT using the rank-1 tensor approximation and propose an L1 norm tensor power iteration solution. In particular, a high order tensor is constructed based on trajectories in the time window, with each tensor element as the affinity of the corresponding trajectory. The assignment variables are the L1 normalized vectors, which are used to approximate the rank-1 tensor. Our approach provides a flexible and effective formulation where both pairwise and high-order association energy can be used expediently. We also show the close relation between our formulation and the multi-dimensional assignment (MDA) model. To solve the optimization in the rank-1 tensor approximation, we propose an algorithm that iteratively powers the intermediate solution followed by an L1 tensor normalization. Aside from effectively capturing high-order motion information, the proposed solver runs efficiently with proved convergence. The experimental validations are conducted on two challenging datasets and our method demonstrates promising performances on both of them.

Haibin Ling received the B.S. degree in mathematics and the MS degree in computer science from Peking University, China, in 1997 and 2000, respectively, and the PhD degree from the University of Maryland, College Park, in Computer Science in 2006. From 2000 to 2001, he was an assistant researcher at Microsoft Research Asia, Beijing, China. From 2006 to 2007, he worked as a postdoctoral scientist at the University of California Los Angeles. After that, he joined Siemens Corporate Research, Princeton, NJ, as a research scientist. Since fall 2008, he has been an Assistant Professor at Temple University. Dr. Ling's research interests include computer vision, medical image analysis, human computer interaction, and machine learning. He received the Best Student Paper Award at the ACM Symposium on User Interface Software and Technology (UIST) in 2003.