Human Action Recognition Based on Depth Image

doi:10.16182/j.issn1004731x.joss.201805003

Journal of System Simulation ›› 2018, Vol. 30 ›› Issue (5): 1641-1649.doi: 10.16182/j.issn1004731x.joss.201805003

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Human Action Recognition Based on Depth Image

Tang Chao¹, Zhang Miaohui^2,*, Li Wei³, Cao Feng⁴, Wang Xiaofeng¹, Tong Xiaohong⁵

1. Department of Computer Scince and Technology, Hefei University, Hefei 230601, China;
2. Energy Research Institute, Jiangxi Academy of Sciences, Nanchang 330096, China;
3. School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China;
4. School of Computer and Information Science, Shanxi University, Taiyuan 030006, China;
5. Information center, Hefei Technology College, Hefei 238000, China

Received:2017-08-19 Revised:2017-09-18 Online:2018-05-08 Published:2019-01-03

Abstract

Abstract: Because of the complexity and non-rigidity of human actions, traditional human action recognition based on RGB video data is a very challenging research topic. According to some deficiencies of existing recognition method based on RGB video data, a novel human action recognition method is proposed based on depth image data. In this new method, the block mean feature in the depth difference motion historical image is fused with the Gabor feature as mixed features and then a rotation forest algorithm is used to model. The experimental results show that the proposed method is simple, fast and efficient compared with other supervised action recognition algorithms on DHA depth datasets.

Key words: human action recognition, depth image, depth difference motion historical image, Gabor feature, rotation forest

CLC Number:

TP391

Tang Chao, Zhang Miaohui, Li Wei, Cao Feng, Wang Xiaofeng, Tong Xiaohong. Human Action Recognition Based on Depth Image[J]. Journal of System Simulation, 2018, 30(5): 1641-1649.

References

[1] LO PRESTI L, LA CASCIA M.3D skeleton-based human action classification: A survey[J]. Pattern Recognition (S0031-3203), 2016, 53: 130-147.
[2] DAS DAWN D, SHAIKH S H.A comprehensive survey of human action recognition with spatio-temporal interest point (STIP) detector[J]. Visual Computer (S0178-2789), 2016, 32(3): 289-306.
[3] ZIAEEFARD M, BERGEVIN R.Semantic human activity recognition: A literature review[J]. Pattern Recognition (S0031-3203), 2015, 48(8): 2329-2345.
[4] LIM C H, VATS E, CHAN C S.Fuzzy human motion analysis: A review[J]. Pattern Recognition (S0031-3203), 2015, 48(5): 1773-1796.
[5] CHEN C, JAFARI R, KEHTARNAVAZ N.A survey of depth and inertial sensor fusion for human action recognition[J]. Multimedia Tools and Applications (S1380-7501), 2017, 76(3): 4405-4425.
[6] CAI Z, HAN J, LIU L, et al.RGB-D datasets using microsoft kinect or similar sensors: a survey[J]. Multimedia Tools and Applications (S1380-7501), 2017, 76(3): 4313-4355.
[7] ZHANG J, LI W, OGUNBONA P O, et al.RGB-D-based action recognition datasets: A survey[J].Pattern Recognition (S0031-3203), 2016, 60: 86-105.
[8] ZHANG B, YANG Y, CHEN C, et al.Action Recognition Using 3D Histograms of Texture and A Multi-Class Boosting Classifier[J]. IEEE Transactions on Image Processing (S1057-7149), 2017, 26(10): 4648-4660.
[9] ZHANG H, ZHONG P, HE J, et al.Combining depth-skeleton feature with sparse coding for action recognition[J]. Neurocomputing (S0925-2312), 2017, 230: 417-426.
[10] YANG Y, DENG C, GAO S, et al.Discriminative Multi-instance Multitask Learning for 3D Action Recognition[J]. IEEE Transactions on Multimedia (S1520-9210), 2017, 19(3): 519-529.
[11] UDDIN M Z.Human activity recognition using segmented body part and body joint features with hidden Markov models[J]. Multimedia Tools and Applications (S1380-7501), 2017, 76(11): 13585-13614.
[12] RAHMANI H, MAHMOOD A, DU H, et al.Histogram of Oriented Principal Components for Cross-View Action Recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence (S0162-8828), 2016, 38(12): 2430-2443.
[13] AKAGUNDUZ E, ASLAN M, SENGUR A, et al.Silhouette Orientation Volumes for Efficient Fall Detection in Depth Videos[J]. IEEE Journal of Biomedical and Health Informatics (S2168-2194), 2017, 21(3): 756-763.
[14] YANG J, YANG J-Y, ZHANG D, et al.Feature fusion: Parallel strategy vs. serial strategy[J]. Pattern Recognition (S0031-3203), 2003, 36(6): 1369-1381.
[15] LLINAS J, HALL D L.Introduction to multi-sensor data fusion[C]// Proc of the 1998 IEEE International Symposium on Circuits and Systems. NEW YORK, NY: IEEE, 2002: 537-540.
[16] RODRIGUEZ J J, KUNCHEVA L I.Rotation forest: A new classifier ensemble method[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence (S0162-8828), 2006, 28(10): 1619-1630.
[17] LIN Y C, HU M C, CHENG W H, et al.Human action recognition and retrieval using sole depth information[C]// Proc of the 20th ACM International Conference on Multimedia. Nara, Japan, 2012: 1053-1056.

Human Action Recognition Based on Depth Image

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