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Titlebook: RGB-D Image Analysis and Processing; Paul L. Rosin,Yu-Kun Lai,Yonghuai Liu Book 2019 Springer Nature Switzerland AG 2019 RGB-D Images.Comp

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發(fā)表于 2025-3-21 16:33:58 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱RGB-D Image Analysis and Processing
編輯Paul L. Rosin,Yu-Kun Lai,Yonghuai Liu
視頻videohttp://file.papertrans.cn/821/820130/820130.mp4
概述Covers the full range of RGB-D imaging: RGB-D data acquisition and processing, RGB-D data analysis, RGB-D applications.Detailed coverage of RGB-D imaging providing technical depth.Each chapter is writ
叢書名稱Advances in Computer Vision and Pattern Recognition
圖書封面Titlebook: RGB-D Image Analysis and Processing;  Paul L. Rosin,Yu-Kun Lai,Yonghuai Liu Book 2019 Springer Nature Switzerland AG 2019 RGB-D Images.Comp
描述.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 qui
出版日期Book 2019
關(guān)鍵詞RGB-D Images; Computer Vision; 3D Shape Analysis; RGB-D Applications; 3D Image Analysis
版次1
doihttps://doi.org/10.1007/978-3-030-28603-3
isbn_softcover978-3-030-28605-7
isbn_ebook978-3-030-28603-3Series ISSN 2191-6586 Series E-ISSN 2191-6594
issn_series 2191-6586
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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https://doi.org/10.1007/978-3-030-28603-3RGB-D Images; Computer Vision; 3D Shape Analysis; RGB-D Applications; 3D Image Analysis
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發(fā)表于 2025-3-22 01:33:43 | 只看該作者
978-3-030-28605-7Springer Nature Switzerland AG 2019
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Commodity RGB-D Sensors: Data Acquisition accessible to a few domain experts, such sensors are nowadays ubiquitous and can even be found in the latest generation of mobile devices, e.g., current smartphones. This democratization of range sensing technology was started with the release of the Microsoft Kinect, and since then many different
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Depth Super-Resolution with Color Guidance: A Reviewns in 3D reconstruction, automotive driver assistance and augmented reality. Due to the easy acquirement of the aligned high-resolution color images, there have been many depth SR approaches with color guidance in the past years. This chapter provides a comprehensive survey of the recent development
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3D Reconstruction from RGB-D Data dynamic scenes, motion of the scene from visual sensors. Recently, low-cost video plus depth (RGB-D) sensors have become widely available and have been applied to 3D reconstruction of both static and dynamic scenes. RGB-D sensors contain an active depth sensor, which provides a stream of depth maps
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