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Human pose estimation using DirectionMaps
2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC), 2018In this paper, we propose a novel approach to detect human pose in a wild image. The approach uses a nonparametric representation, which we refer as DirectionMaps, to learn the direction information of human body parts. The whole architecture is divided into two stages.
Wenlin Zhuang, Siyu Xia, Yangang Wang
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3D Human Pose Estimation with 2D Human Pose and Depthmap
2020Three-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 +4 more
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2015
The aim of human pose estimation is to detect and estimate the configuration of the articulation structure of a person. Human pose estimation has become a popular research topic including a wide range of approaches. Marker-based approaches, for example, are one of the most precise methods, but they need special markers attached to the human body.
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The aim of human pose estimation is to detect and estimate the configuration of the articulation structure of a person. Human pose estimation has become a popular research topic including a wide range of approaches. Marker-based approaches, for example, are one of the most precise methods, but they need special markers attached to the human body.
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Human Pose Estimation Using Consistent Max Covering
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009A novel consistent max-covering method is proposed for human pose estimation. We focus on problems in which a rough foreground estimation is available. Pose estimation is formulated as a jigsaw puzzle problem in which the body part tiles maximally cover the foreground region, match local image features, and satisfy body plan and color constraints. This
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International Scientific Journal of Engineering and Management
In "Human Pose Estimation" with integrated feedback mechanisms to assess and guide users in achieving correct poses. Utilizing advanced deep learning techniques in computer vision, the system swiftly detects key points on the human body and provides instant feedback on pose accuracy.
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In "Human Pose Estimation" with integrated feedback mechanisms to assess and guide users in achieving correct poses. Utilizing advanced deep learning techniques in computer vision, the system swiftly detects key points on the human body and provides instant feedback on pose accuracy.
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Human Pose Estimation and Tracking
2016Human pose estimation and tracking is one of the most intriguing yet challenging applications of consumer depth cameras. After an overview of common human hand and body models, we introduce approaches for pose recovery from a single frame, starting from the popular method based on Random Decision Forests proposed by Shotton et al.
Pietro Zanuttigh +5 more
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Camera Pose Estimation using Human Head Pose Estimation
Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2022Robert Fischer +2 more
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Human Pose Estimation from Video and IMUs
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016In this work, we present an approach to fuse video with sparse orientation data obtained from inertial sensors to improve and stabilize full-body human motion capture. Even though video data is a strong cue for motion analysis, tracking artifacts occur frequently due to ambiguities in the images, rapid motions, occlusions or noise.
Timo von Marcard +2 more
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Hierarchical pose estimation for human gait analysis
Computer Methods and Programs in Biomedicine, 2012Articulated structures like the human body have many degrees of freedom. This makes an evaluation of the configuration's likelihood very challenging. In this work we propose new linked hierarchical graphical models which are able to efficiently evaluate likelihoods of articulated structures by sharing visual primitives.
Jens, Spehr +2 more
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Bilateral Pose Transformer for Human Pose Estimation
Proceedings of the 4th International Symposium on Signal Processing Systems, 2022Chia Chen Yen, Tao Pin, Hongmin Xu
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