Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
A requirement common to most dynamic vision applications is the ability to track objects in a sequence of frames. This problem has been extensively studied in the past few years, ...
Octavia I. Camps, Hwasup Lim, Cecilia Mazzaro, Mar...
Color-based trackers recently proposed in [3,4,5] have been proved robust and versatile for a modest computational cost. They are especially appealing for tracking tasks where the ...
Carine Hue, Jaco Vermaak, Michel Gangnet, Patrick ...
Time and streak surfaces are ideal tools to illustrate time-varying vector fields since they directly appeal to the intuition about coherently moving particles. However, efficient ...
We propose a sequential Monte Carlo data association algorithm based on a two-level computational framework for tracking varying number of interacting objects in dynamic scene. Fi...