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Human pose analysisdeep learning meets human kinematics in video /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Human pose analysisby Songlin Du, Takeshi Ikenaga.
其他題名:	deep learning meets human kinematics in video /
作者:	Du, Songlin.
其他作者:	Ikenaga, Takeshi.
出版者:	Singapore :Springer Nature Singapore :2025.
面頁冊數:	xiv, 208 p. :ill. (chiefly color), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Computer vision.
電子資源:	https://doi.org/10.1007/978-981-97-9334-1
ISBN:	9789819793341$q(electronic bk.)

Human pose analysisdeep learning meets human kinematics in video /
Du, Songlin.

Human pose analysisdeep learning meets human kinematics in video /[electronic resource] :by Songlin Du, Takeshi Ikenaga. - Singapore :Springer Nature Singapore :2025. - xiv, 208 p. :ill. (chiefly color), digital ;24 cm.

Chapter 1. Introduction -- Chapter 2. Bidirectionally Learning Heatmaps for 2D Human Pose Estimation -- Chapter 3. Self-Supervised Multi-Person 2D Human Pose Estimation -- Chapter 4. Bidirectional 2D-3D Transformation for 3D Human Pose Estimation -- Chapter 5. Joint Data Augmentation and Representation for 3D Human Pose Estimation -- Chapter 6. Spatial-Temporal Feature Transform for 3D Human Pose Estimation -- Chapter 7. Real-Time 3D Human Pose Estimation from a Single RGB Image -- Chapter 8. Spatio-Temporal Aggregation for 3D Human Head Pose Estimation -- Chapter 9. Spatial-Temporal Pyramid for 3D Human Head Pose Prediction -- Chapter 10. Conclusion and Outlook.

This book stands at the intersection of computer vision, artificial intelligence, and human kinematics, offering a comprehensive exploration of the principles, methodologies, and applications of human pose analysis in video data. It covers two main aspects: human body pose analysis and human head pose analysis. Human body pose analysis involves estimating the position and orientation of major joints and body parts, such as the head, neck, shoulders, elbows, wrists, hips, knees, and ankles, to capture the entire body posture in 2D or 3D space. In contrast, human head pose analysis focuses solely on the head's orientation, typically estimating the angles of rotation around the yaw, pitch, and roll axes to determine the direction in which a person is looking or tilting their head. The book is divided into three parts, each detailing recent research in different areas of pose analysis. The first chapter provides an overview of human body and head pose analysis, including the fundamental principles of kinematic representation, as well as commonly used datasets and evaluation metrics. The first part, consisting of Chapters 2 and 3, delves into 2D human body pose analysis. The second part, spanning Chapters 4 through 7, covers the latest advancements in 3D human body pose estimation, focusing on inferring 3D positions and orientations of body joints from 2D images or videos. The third part, covering Chapters 8 and 9, presents recent studies on 3D human head pose analysis, encompassing both 3D head pose estimation and prediction. The final chapter concludes by summarizing the techniques discussed and outlining future research directions and applications in human body and head pose analysis.

ISBN: 9789819793341$q(electronic bk.)

Standard No.: 10.1007/978-981-97-9334-1doiSubjects--Topical Terms:

200113
Computer vision.

LC Class. No.: TA1634 / .D87 2025

Dewey Class. No.: 006.37

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505 0 $a Chapter 1. Introduction -- Chapter 2. Bidirectionally Learning Heatmaps for 2D Human Pose Estimation -- Chapter 3. Self-Supervised Multi-Person 2D Human Pose Estimation -- Chapter 4. Bidirectional 2D-3D Transformation for 3D Human Pose Estimation -- Chapter 5. Joint Data Augmentation and Representation for 3D Human Pose Estimation -- Chapter 6. Spatial-Temporal Feature Transform for 3D Human Pose Estimation -- Chapter 7. Real-Time 3D Human Pose Estimation from a Single RGB Image -- Chapter 8. Spatio-Temporal Aggregation for 3D Human Head Pose Estimation -- Chapter 9. Spatial-Temporal Pyramid for 3D Human Head Pose Prediction -- Chapter 10. Conclusion and Outlook.
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