Real-time Multiple People Tracking with Deeply Learned Candidate Selection and Person Re-Identification

Online multi-object tracking is a fundamental problem in time-critical video analysis applications. A major challenge in the popular tracking-by-detection framework is how to associate unreliable detection results with existing tracks. In this paper, we propose to handle unreliable detection by collecting candidates from outputs of both detection and tracking. The intuition behind generating redundant candidates is that detection and tracks can complement each other in different scenarios. Detection results of high confidence prevent tracking drifts in the long term, and predictions of tracks can handle noisy detection caused by occlusion. In order to apply optimal selection from a considerable amount of candidates in real-time, we present a novel scoring function based on a fully convolutional neural network, that shares most computations on the entire image. Moreover, we adopt a deeply learned appearance representation, which is trained on large-scale person re-identification datasets, to improve the identification ability of our tracker. Extensive experiments show that our tracker achieves real-time and state-of-the-art performance on a widely used people tracking benchmark.Comment: ICME 201

Experimental characterization of the PT asymmetry with balanced inflow and outflow at different Reynolds numbers

This research focused on characterizing the PT asymmetry with balanced inflow and outflow conditions at different Reynolds number using experimental method. The characterization process utilized PIV data to explore the relationship between PT asymmetry and Reynolds number in two different experiments. In the first experiment, balanced inflow and outflow are used to generate the flow field in a cuboid test section with different Reynolds number, the inflow and outflow are located at the central of left side and right side of the test section. In the second experiment, a main flow is introduced to the first experiment by adding another inflow and outflow which locate at a symmetric position on the bottom side of the test section. The flow field is generated by the two inflows and outflows with different Reynolds number. The results show that there is a linear relationship between PT asymmetry and Reynolds number when Reynolds number is less than 200 for a balanced inflow/outflow situation. They also show that there is a decreasing trend of PTasymmetry when Reynolds number increases for balanced inflow/outflow combined with main flow