Human motion detection using Markov random fields

被引：6

作者：

Cao, Xiao-Qin ^{[1
]}

Liu, Zhi-Qiang ^{[1
]}

机构：

[1] City Univ Hong Kong, Sch Creat Media, Kowloon Tong, Hong Kong, Peoples R China

来源：

JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING | 2010年 / 1卷 / 03期

关键词：

Human motion; Markov random fields; Relaxation labeling; HUMAN POSE; TRACKING; MODEL;

D O I：

10.1007/s12652-010-0015-1

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose Markov random fields (MRFs) to automatically detect a moving human body through minimizing the joint energy of the MRF for the velocity and relative position of body parts. The relaxation labeling algorithm is employed to find the best body part labeling configuration between MRFs and observed data. We detect a walking motion viewed monocularly based on point features, where some points are from the unoccluded body parts and some belong to the background. The results show that MRFs can detect human motions robustly and accurately.

引用

页码：211 / 220

页数：10

共 50 条

[11] Car detection using Markov random fields on geometric features
Chang, Xingzhi
Gao, Liqun
PROCEEDINGS OF THE 46TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-14, 2007, : 2108 - 2113
[12] Segmentation of motion textures using mixed-state Markov random fields
Crivelli, T.
Cernuschi-Frias, B.
Bouthemy, P.
Yao, J. F.
MATHEMATICS OF DATA IMAGE PATTERN RECOGNITION, COMPRESSION, AND ENCRYPTION WITH APPLICATIONS IX, 2006, 6315
[13] Detection of spatiotemporally coherent rainfall anomalies using Markov Random Fields
Mitra, Adway
Seshadri, Ashwin K.
COMPUTERS & GEOSCIENCES, 2019, 122 : 45 - 53
[14] ColluEagle: collusive review spammer detection using Markov random fields
Wang, Zhuo
Hu, Runlong
Chen, Qian
Gao, Pei
Xu, Xiaowei
DATA MINING AND KNOWLEDGE DISCOVERY, 2020, 34 (06) : 1621 - 1641
[15] ColluEagle: collusive review spammer detection using Markov random fields
Zhuo Wang
Runlong Hu
Qian Chen
Pei Gao
Xiaowei Xu
Data Mining and Knowledge Discovery, 2020, 34 : 1621 - 1641
[16] Direct estimate of motion parameters by means of Markov random fields
Bartolini, F
Caldelli, R
Romagnoli, V
2001 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL II, PROCEEDINGS, 2001, : 949 - 952
[17] Markov random fields and block matching for multiresolution motion estimation
Leconge, R
Laligant, O
Truchetet, F
HIGH-SPEED IMAGING AND SEQUENCE ANALYSIS II, 2000, 3968 : 10 - 21
[18] Clutter modeling for subsurface detection in hyperspectral imagery using Markov random fields
Masalmah, YM
Vélez-Reyes, M
Jiménez-Rodríguez, LO
IMAGING SPECTROMETRY IX, 2003, 5159 : 52 - 63
[19] Micro calcification clusters detection by using gaussian markov random fields representation
Zhang, Xinsheng
Luo, Zhengshan
Wang, Minghu
Research Journal of Applied Sciences, Engineering and Technology, 2012, 4 (18) : 3425 - 3431
[20] Collective Activity Detection using Hinge-loss Markov Random Fields
London, Ben
Khamis, Sameh
Bach, Stephen H.
Huang, Bert
Getoor, Lise
Davis, Larry
2013 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW), 2013, : 566 - 571

← 1 2 3 4 5 →