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ICMCS
2007
IEEE

Tracking Multiple Objects using Probability Hypothesis Density Filter and Color Measurements

10 years 9 months ago
Tracking Multiple Objects using Probability Hypothesis Density Filter and Color Measurements
Most methods for multiple object tracking in video represent the state of multi-objects in a high dimensional joint state space. This leads to high computational complexity. This paper presents a method using the probability hypothesis density (PHD) filter to estimate the state of multiple objects in video. The method operates on the single object state space instead of the joint state space. A PHD recursion for visual observations with color measurements is proposed. Our method can track varying number of objects.
Nam Trung Pham, Weimin Huang, Sim Heng Ong
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where ICMCS
Authors Nam Trung Pham, Weimin Huang, Sim Heng Ong
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