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Sensors 2015, 15(3), 5197-5227; doi:10.3390/s150305197

Continuous Human Action Recognition Using Depth-MHI-HOG and a Spotter Model

1
School of Electrical and Electronic Engineering, Yonsei University, 134 Shinchon-Dong, Seodaemun-Gu, Seoul 120-749, Korea
2
Department of Electrical Engineering, Suwon Science College, Hwaseong 445-742, Korea
3
Department of Electrical, Electronic and Control Engineering, Hankyong National University, Anseong 456-749, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Gonzalo Pajares Martinsanz
Received: 19 September 2014 / Revised: 30 January 2015 / Accepted: 4 February 2015 / Published: 3 March 2015
(This article belongs to the Section Physical Sensors)

Abstract

In this paper, we propose a new method for spotting and recognizing continuous human actions using a vision sensor. The method is comprised of depth-MHI-HOG (DMH), action modeling, action spotting, and recognition. First, to effectively separate the foreground from background, we propose a method called DMH. It includes a standard structure for segmenting images and extracting features by using depth information, MHI, and HOG. Second, action modeling is performed to model various actions using extracted features. The modeling of actions is performed by creating sequences of actions through k-means clustering; these sequences constitute HMM input. Third, a method of action spotting is proposed to filter meaningless actions from continuous actions and to identify precise start and end points of actions. By employing the spotter model, the proposed method improves action recognition performance. Finally, the proposed method recognizes actions based on start and end points. We evaluate recognition performance by employing the proposed method to obtain and compare probabilities by applying input sequences in action models and the spotter model. Through various experiments, we demonstrate that the proposed method is efficient for recognizing continuous human actions in real environments. View Full-Text
Keywords: continuous human action recognition; depth-MHI-HOG (DMH); hidden Markov model; action modeling; action spotting; spotter model continuous human action recognition; depth-MHI-HOG (DMH); hidden Markov model; action modeling; action spotting; spotter model
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Eum, H.; Yoon, C.; Lee, H.; Park, M. Continuous Human Action Recognition Using Depth-MHI-HOG and a Spotter Model. Sensors 2015, 15, 5197-5227.

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