Depth video based human model reconstruction resolving self-occlusion

Tracking movements of the body in a natural living environment of a person is a challenging undertaking. Such tracking information can be used as a part of detecting any onsets of anomalies in movement patterns or as a part of a remote monitoring environment. The tracking information can be mapped and visualized using a virtual avatar model of the tracked person. This paper presents an initial novel experimental study of using a commercially available deep-learning body tracking system based on an RGB-D sensor for virtual human model reconstruction. We carried out our study in an indoor environment under natural conditions. To study the performance of the tracker, we experimentally study the output of the tracker which is in the form of a skeleton (stick-figure) data structure under several conditions in order to observe its robustness and identify its drawbacks. In addition, we show and study how the generic model can be mapped for virtual human model reconstruction. It was found that the deep-learning tracking approach using an RGB-D sensor is susceptible to various environmental factors which result in the absence and presence of noise in estimating the resulting locations of skeleton joints. This as a result introduces challenges for further virtual model reconstruction. We present an initial approach for compensating for such noise resulting in a better temporal variation of the joint coordinates in the captured skeleton data. We explored how the extracted joint position information of the skeleton data can be used as a part of the virtual human model reconstruction.

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Comparative Psychosocial Pathology: A Human Model of Primate Abusive Behavior

Contemporary Psychology ◽

10.1037/025182 ◽

1984 ◽

Vol 29 (10) ◽

pp. 781-782

Author(s):

Gene P. Sackett ◽

David V. Baldwin

Keyword(s):

Human Model ◽

Abusive Behavior

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Modern Technology for Image processing and Computer vision -A Review

Journal of Advanced Sciences and Engineering Technologies ◽

10.32441/jaset.v1i2.178 ◽

2018 ◽

Vol 1 (2) ◽

pp. 17-23

Author(s):

Takialddin Al Smadi

Keyword(s):

Image Processing ◽

Computer Vision ◽

Augmented Reality ◽

Video Compression ◽

Video Processing ◽

Vision System ◽

Citrus Fruit ◽

Modern Technology ◽

Image And Video Processing ◽

Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality. © 2018 JASET, International Scholars and Researchers Association

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