Multi-view human action recognition system employing 2DPCA

Naiel, Mohamed A.; Abdelwahab, Moataz M.; El-Saban, Motaz

doi:10.1109/wacv.2011.5711513

Cited by 19 publications

(5 citation statements)

References 17 publications

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“…Commonly, the best view is chosen based on some input/output criteria as the view with the biggest region of interest [ 16 ], the highest probability of feature matching [ 17 ] or the highest accuracy obtained during training [ 18 ]. In [ 19 ], Naiel et al used a majority voting technique, where the camera with a minimum distance is chosen when no majority is reached. In this work, the well-known motion history and energy images (MHI, MEI) from [ 20 ] are reduced with a two-dimensional principal component analysis (PCA) and classified based on a k-nearest neighbour classifier.…”

Section: Related Workmentioning

confidence: 99%

A Vision-Based System for Intelligent Monitoring: Human Behaviour Analysis and Privacy by Context

Chaaraoui

Padilla-López

Ferrández-Pastor

et al. 2014

Sensors

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Due to progress and demographic change, society is facing a crucial challenge related to increased life expectancy and a higher number of people in situations of dependency. As a consequence, there exists a significant demand for support systems for personal autonomy. This article outlines the vision@home project, whose goal is to extend independent living at home for elderly and impaired people, providing care and safety services by means of vision-based monitoring. Different kinds of ambient-assisted living services are supported, from the detection of home accidents, to telecare services. In this contribution, the specification of the system is presented, and novel contributions are made regarding human behaviour analysis and privacy protection. By means of a multi-view setup of cameras, people's behaviour is recognised based on human action recognition. For this purpose, a weighted feature fusion scheme is proposed to learn from multiple views. In order to protect the right to privacy of the inhabitants when a remote connection occurs, a privacy-by-context method is proposed. The experimental results of the behaviour recognition method show an outstanding performance, as well as support for multi-view scenarios and real-time execution, which are required in order to provide the proposed services.

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Section: Related Workmentioning

confidence: 99%

A Vision-Based System for Intelligent Monitoring: Human Behaviour Analysis and Privacy by Context

Chaaraoui

Padilla-López

Ferrández-Pastor

et al. 2014

Sensors

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show abstract

“…In the experiments, we compared the proposed method with Hough forests and the methods of Yan and colleagues , Naiel and colleagues , and Zhu and colleagues . In contrast with the proposed method, Hough forests are applied to single‐view video, not multiview video.…”

Section: Evaluation Experimentsmentioning

confidence: 99%

“…In the experiments, the random forest parameters were set as follows: number of trees K = 100, maximum tree depth N n = 25, minimum number of local patches assigned to nodes N n = 30, number of generated discriminant functions N b = 1000. In addition, the parameters of the spatiotemporal local features were set as follows: In the experiments, we compared the proposed method with Hough forests and the methods of Yan and colleagues [10], Naiel and colleagues [4], and Zhu and colleagues [13]. In contrast with the proposed method, Hough forests are applied to single-view video, not multiview video.…”

Section: Evaluation Experimentsmentioning

confidence: 99%

“…In conventional multiview action recognition requiring human detection and tracking, the outputs of every view are integrated mostly by majority vote. Naiel and colleagues proposed a method in which a discriminator is trained for each view, and then a majority vote is applied to the outputs to recognize actions . Yan and colleagues implemented multiview action recognition by using a weighted majority vote of the output .…”

Section: Related Researchmentioning

confidence: 99%

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Simultaneous Recognition of Human Action and Its Location Estimation Based on Multiview Hough Voting

Hara

Hirayama

Mase

2015

Elect Comm in Japan

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SUMMARY Remote surveillance of large‐scale equipment such as power plants and building complexes is important to prevent serious attacks and troubles. Automatic human action recognition can reduce the burdens of the surveillance. Multiview video is useful for human action recognition, because it provides robustness to the changes of people's appearance by orientation and occlusion. One problem of conventional multiview action recognition is that it requires both detection and tracking before action recognition. Human pose and motion vary depending on the person's action, and such variances may cause detection and tracking error. To solve this problem, previous work has proposed simultaneous action recognition and location estimation for single‐view videos using Hough voting. In this paper, we extend the Hough voting approach to simultaneous multiview action recognition and location estimation. Our proposed method independently casts votes for the action labels and spatiotemporal reference positions of actions in each view and integrates them using homographical transformations in the multiview extension. We evaluated our method and confirmed that it achieved high accuracy in action recognition and location estimation. The contribution of this paper is that it enables multiview action recognition without prior human detection and tracking.

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“…Majority voting has been the most common technique for the fusion of decisions [15,16]. A weighted voting strategy has been proposed in [28], correcting each vote according to the value of the observed feature.…”

Section: Human Action Recognition From Multiple Cameras and Dasarathymentioning

confidence: 99%

A Data Fusion Perspective on Human Motion Analysis Including Multiple Camera Applications

Cilla

Patricio

Berlanga

2013

Natural and Artificial Computation in Engineering and Medical Applications

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Abstract. Human motion analysis methods have received increasing attention during the last two decades. In parallel, data fusion technologies have emerged as a powerful tool for the estimation of properties of objects in the real world. This papers presents a view of human motion analysis from the viewpoint of data fusion. JDL process model and Dasarathy's input-output hierarchy are employed to categorize the works in the area. A survey of the literature in human motion analysis from multiple cameras is included. Future research directions in the area are identified after this review.

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Multi-view human action recognition system employing 2DPCA

Cited by 19 publications

References 17 publications

A Vision-Based System for Intelligent Monitoring: Human Behaviour Analysis and Privacy by Context

A Vision-Based System for Intelligent Monitoring: Human Behaviour Analysis and Privacy by Context

Simultaneous Recognition of Human Action and Its Location Estimation Based on Multiview Hough Voting

A Data Fusion Perspective on Human Motion Analysis Including Multiple Camera Applications

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