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FAST DETECTION OF INDEPENDENT MOTION IN CROWDS GUIDED BY SUPERVISED LEARNING
 

Summary: FAST DETECTION OF INDEPENDENT MOTION IN CROWDS
GUIDED BY SUPERVISED LEARNING
Yuan Li, Haizhou Ai
Computer Science and Technology Department, Tsinghua University, Beijing 100084, China
E-mail: ahz@mail.tsinghua.edu.cn
ABSTRACT
Different from appearance-based methods, clustering fea-
ture points only by their motion coherence is an emerging
category of approach to detecting and tracking individuals
among crowds. This paper reformalizes the problem and mod-
els a novel objective function for clustering with potential
functions as in conditional random field approach. The merits
include: 1) it integrates motion, spatial, temporal information;
2) the parameters are automatically obtained by supervised
learning; 3) the objective function is based on feature-pair in-
formation, which enables effective learning on small amount
of training data, as well as very fast online processing speed.
Detection ROC curves are given on several datasets (includ-
ing the CAVIAR set).
Index Terms-- Motion detection, multi-object tracking,

  

Source: Ai, Haizhou - Department of Computer Science and Technology, Tsinghua University

 

Collections: Computer Technologies and Information Sciences