Exploring Rare Pose in Human Pose Estimation
نویسندگان
چکیده
منابع مشابه
Human Pose Estimation
Human pose estimation is one of the key problems in computer vision that has been studied for well over 15 years. The reason for its importance is the abundance of applications that can benefit from such a technology. For example, human pose estimation allows for higher level reasoning in the context of humancomputer interaction and activity recognition; it is also one of the basic building blo...
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Human pose estimation is the task of estimating the joint locations of one or multiple people within an image. It is a core challenge in computer vision because it forms the foundation of more complex tasks such as activity recognition and motion planning. For example, joint locations have been used to supplement other visual features to determine the trajectory of a person through a sequence o...
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Automatic human motion capture is an important and significant problem in the computer vision community. A successful system may have many applications including inexpensive motion capture and analysis in unconstrained environments, human-computer interfaces, and automatic surveillance systems. This work focuses on an important sub-problem in computer vision based motion capture: monocular huma...
متن کاملClustered Pose and Nonlinear Appearance Models for Human Pose Estimation
Human pose estimation is the task of estimating the ‘pose’ or configuration of a person’s body parts e.g. labeling the position and orientation of the head, torso, arms and legs in an image. In this paper we propose an extension of the pictorial structure model (PSM) approach [2]. Our method incorporates richer models of appearance and prior over pose without introducing unacceptable computatio...
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We investigate the task of 2D articulated human pose estimation in unconstrained still images. This is extremely challenging because of variation in pose, anatomy, clothing, and imaging conditions. Current methods use simple models of body part appearance and plausible configurations due to limitations of available training data and constraints on computational expense. We show that such models...
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2020
ISSN: 2169-3536
DOI: 10.1109/access.2020.3033531