RGB-D image analysis and processing

• 其他作者：
  • Rosin, Paul L., editor.
  • Lai, Yu-Kun, editor.
  • Shao, Ling, editor.
  • Liu, Yonghuai, editor.
  • SpringerLink (Online service)
• 其他題名：
  • Advances in computer vision and pattern recognition.
• 出版： Cham : Springer International Publishing :Imprint: Springer
• 叢書名： Advances in computer vision and pattern recognition,
• 主題： Image analysis. , Image processing. , Image Processing and Computer Vision. , User Interfaces and Human Computer Interaction. , Artificial Intelligence.
• ISBN： 9783030286033 (electronic bk.) 、 9783030286026 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: Part I RGB-D Data Acquisition and Processing -- RGB-D Sensors: Data Acquisition -- Dealing with Missing Depth: Recent Advances in Depth Image Completion and Estimation -- Depth Super-resolution With Color Guidance: A Review -- RGB-D Sensors Data Quality Assessment and Improvement for Advanced Applications -- 3D Reconstruction from RGB-D Data -- RGB-D Odometry and SLAM -- Enhancing 3D Capture with Multiple Depth Camera Systems: A State-of-the-Art Report -- Part II RGB-D Data Analysis -- RGB-D Image-based Object Detection: from Traditional Methods to Deep Learning Techniques -- RGB-S Salient Object Detection: A Review -- Foreground Detection and segmentation in RGB-D Images -- Instance- and Category-level 6d Object Pose Estimation -- Part III RGB-D Applications -- Semantic RGB-D Perception for Cognitive Service Robots -- RGB-D Sensors and Signal Processing for Fall Detection -- RGB-D Interactive Systems on Serious Games for Motor Rehabilitation Therapy and Therapeutic Measurements -- Real-Time Hand Pose Estimation using Depth Camera -- RGB-D Object Classification for Autonomous Driving Perception -- People Counting in Crowded Environment and Re-identification -- References -- Index.
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• 摘要註: This book focuses on the fundamentals and recent advances in RGB-D imaging as well as covering a range of RGB-D applications. The topics covered include: data acquisition, data quality assessment, filling holes, 3D reconstruction, SLAM, multiple depth camera systems, segmentation, object detection, salience detection, pose estimation, geometric modelling, fall detection, autonomous driving, motor rehabilitation therapy, people counting and cognitive service robots. The availability of cheap RGB-D sensors has led to an explosion over the last five years in the capture and application of colour plus depth data. The addition of depth data to regular RGB images vastly increases the range of applications, and has resulted in a demand for robust and real-time processing of RGB-D data. There remain many technical challenges, and RGB-D image processing is an ongoing research area. This book covers the full state of the art, and consists of a series of chapters by internationally renowned experts in the field. Each chapter is written so as to provide a detailed overview of that topic. RGB-D Image Analysis and Processing will enable both students and professional developers alike to quickly get up to speed with contemporary techniques, and apply RGB-D imaging in their own projects.
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