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Vision-Based Hand Function Evaluation with Soft Robotic Rehabilitation Glove. [PDF]

Sensors (Basel)
Tong M, Cheung M, Lei Y, Villarroel M, He L.   +4 more
europepmc   +1 more source

Reliability assessment of markerless technologies in biomechanical motion analysis: a performance comparison. [PDF]

Front Sports Act Living
Balci IC, Sayin I, Salturk S, Gursoy R, Ozsoy U, Dogru HC, Akca G, Eraslan A, Sahin O, Demircali AA, Uvet H.   +10 more
europepmc   +1 more source

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3D human body pose estimation by SuperQuadrics

Proceedings of the International Conference on Computer Vision Theory and Applications, 2012
This paper presents a method for 3D Human Body pose estimation. 3D real data of the searched object is acquired by a multi-camera system and segmented by a special preprocessing algorithm based on clothing analysis. The human body model is built by nine SuperQuadrics (SQ) with a-priori known anthropometric scaling and shape parameters.
I. Afanasyev, Lunardelli, Massimo, N. Biasi, Baglivo, Luca, Tavernini, Mattia, Setti, Francesco, De Cecco, Mariolino   +6 more
openaire   +4 more sources

3D Human Pose Estimation with 2D Human Pose and Depthmap

2020
Three-dimensional human pose estimation models are conventionally based on RGB images or by assuming that accurately-estimated (near to ground truth) 2D human pose landmarks are available. Naturally, such data only contains information about two dimensions, while the 3D poses require the three dimensions of height, width, and depth.
Zhiheng Zhou, Yue Cao, Xuanying Zhu, Henry Gardner, Hongdong Li   +4 more
openaire   +1 more source

3D Pictorial Structures Revisited: Multiple Human Pose Estimation

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016
We address the problem of 3D pose estimation of multiple humans from multiple views. The transition from single to multiple human pose estimation and from the 2D to 3D space is challenging due to a much larger state space, occlusions and across-view ambiguities when not knowing the identity of the humans in advance.
Vasileios Belagiannis, Sikandar Amin, Mykhaylo Andriluka, Bernt Schiele, Nassir Navab, Slobodan Ilic   +5 more
openaire   +3 more sources

3D Human Pose Estimation Using RGBD Camera

2021 IEEE International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI), 2021
This work addresses a method to map the estimated 2D pose from a color image to 3D pose and obtain more accurate 3D keypoints. In this paper, the RGBD camera is used to simultaneously acquire color images and depth images. AlphaPose is used to estimate the 2D keypoints of the target, and the 2D keypoints are mapped to the corresponding depth maps to ...
Zhenghui Fang, Anna Wang, Chunguang Bu, Chen Liu   +3 more
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3D Human Pose Estimation with Adversarial Learning

2019 International Conference on Virtual Reality and Visualization (ICVRV), 2019
In recent years, due to the deep learning and the development of computer vision, great progress has been made in the 3D human pose estimation from RGB images. However, due to the lack of depth information in RGB images, this task still faces great challenges.
Wenming Meng, Tao Hu, Shuai Li
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3D Human Pose Estimation Using WiFi Signals

Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems, 2021
This paper presents GoPose, a 3D skeleton-based human pose estimation system that uses commodity WiFi devices at home. Our system leverages the WiFi signals reflected off the human body for 3D pose estimation. In contrast to prior systems that need dedicated sensors, our system does not require a user to wear any sensors and can reuse the WiFi devices ...
Yili Ren, Zi Wang, Yichao Wang, Sheng Tan, Yingying Chen, Jie Yang   +5 more
openaire   +1 more source