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    Regression-based convolutional 3D pose estimation from single image

    , Article Electronics Letters ; Volume 54, Issue 5 , March , 2018 , Pages 292-293 ; 00135194 (ISSN) Ershadi Nasab, S ; Kasaei, S ; Sanaei, E ; Sharif University of Technology
    Institution of Engineering and Technology  2018
    Abstract
    Estimation of 3D human pose from a single image is a challenging task because of ambiguities in projection from 3D space to the 2D image plane. A new two-stage deep convolutional neural network-based method is proposed for regressing the distance and angular difference matrices among body joints. Using the angular difference between body joints in addition to the distance between them in articulated objects such as human body can better model the structure of the shapes and increases the modelling capability of the learning method. Experimental results on HumanEva I and Human3.6M datasets show that the proposed method has substantial improvement in the mean per joint position error measure... 

    Uncalibrated multi-view multiple humans association and 3D pose estimation by adversarial learning

    , Article Multimedia Tools and Applications ; Volume 80, Issue 2 , 2021 , Pages 2461-2488 ; 13807501 (ISSN) Ershadi Nasab, S ; Kasaei, S ; Sanaei, E ; Sharif University of Technology
    Springer  2021
    Abstract
    Multiple human 3D pose estimation is a useful but challenging task in computer vison applications. The ambiguities in estimation of 2D and 3D poses of multiple persons can be verified by using multi-view frames, in which the occluded or self-occluded body parts of some persons might be visible in other camera views. But, when cameras are moving and uncalibrated, estimating the association of multiple human body parts among different camera views is a challenging task. This paper presents novel methods for multiple human 3D pose estimation and pose association in multi-view camera frames in an uncalibrated camera setup using an adversarial learning framework. The generator is a 3D pose... 

    Uncalibrated multi-view multiple humans association and 3D pose estimation by adversarial learning

    , Article Multimedia Tools and Applications ; 2020 Ershadi Nasab, S ; Kasaei, S ; Sanaei, E ; Sharif University of Technology
    Springer  2020
    Abstract
    Multiple human 3D pose estimation is a useful but challenging task in computer vison applications. The ambiguities in estimation of 2D and 3D poses of multiple persons can be verified by using multi-view frames, in which the occluded or self-occluded body parts of some persons might be visible in other camera views. But, when cameras are moving and uncalibrated, estimating the association of multiple human body parts among different camera views is a challenging task. This paper presents novel methods for multiple human 3D pose estimation and pose association in multi-view camera frames in an uncalibrated camera setup using an adversarial learning framework. The generator is a 3D pose...