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Summary: Tracking in Low Frame Rate Video: A Cascade Particle Filter with
Discriminative Observers of Different Lifespans
Yuan Li, Haizhou Ai
Computer Science and Technology Dept.
Tsinghua University, Beijing, China
ahz@mail.tsinghua.edu.cn
Takayoshi Yamashita, Shihong Lao, Masato Kawade
Sensing and Control Technology Laboratory
Omron Corporation, Kyoto, Japan
{takayosi|lao|kawade}@ari.ncl.omron.co.jp
Abstract
Tracking object in low frame rate video or with abrupt
motion poses two main difficulties which conventional
tracking methods can barely handle: 1) poor motion conti-
nuity and increased search space; 2) fast appearance varia-
tion of target and more background clutter due to increased
search space. In this paper, we address the problem from a
view which integrates conventional tracking and detection,
and present a temporal probabilistic combination of dis-
criminative observers of different lifespans. Each observer
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