Crowd Behavior Classification based on Generic Descriptors

被引：1

作者：

Wong, Pei Voon ^{[1
]}

Mustapha, Norwati ^{[2
]}

Affendey, Lilly Suriani ^{[2
]}

Khalid, Fatimah ^{[2
]}

Chen, Yen-Lin ^{[3
]}

机构：

[1] Univ Tunku Abdul Rahman, Fac Informat & Commun Technol, Kampar 31900, Perak, Malaysia

[2] Univ Putra Malaysia, Fac Comp Sci & Informat Technol, Serdang 43400, Selangor, Malaysia

[3] Natl Taipei Univ Technol, Dept Comp Sci & Informat Engn, 1,Sec 3,Chung Hsiao E Rd, Taipei 10608, Taiwan

来源：

2019 INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING AND COMMUNICATION SYSTEMS (ISPACS) | 2019年

关键词：

Crowd behavior classification; generic descriptors; crowded scenes; group-level; motion;

D O I：

10.1109/ispacs48206.2019.8986333

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Crowd behavior analysis plays an important role in high security interests in public areas such as railway stations, shopping centres, and airports, where large populations gather. The crowded scenes vary in various densities, structures and occlusion. It brings enormous challenges in identifying generic descriptors to describe motion dynamics caused by pedestrians walk in different directions with extremely diverse behaviors. Therefore, this research is proposal an approach for crowd behavior analysis to recognize the common properties across different crowded scenes. The recognized common properties are then used to identify generic descriptors from group-level for crowd behavior classification.

引用

页数：2

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