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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RGB-D Odometry and SLAM. They are low-cost, low-power, and low-size alternatives to traditional range sensors such as LiDAR. Moreover, unlike RGB cameras, RGB-D sensors provide the additional depth information that removes the need of frame-by-frame triangulation for 3D scene reconstruction. These merits have made them ve

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Foreground Detection and Segmentation in RGB-D Imagesmmunity, foreground detection and segmentation for RGB-D images have gained a lot of research interest in the past years. In this chapter, an overview of some foreground-based tasks in RGB-D images is provided, including saliency detection, co-saliency detection, foreground segmentation, and co-segm

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Instance- and Category-Level 6D Object Pose Estimationuch as robotics and augmented reality. To recover poses from objects that have been seen in advance, instance-level methods have been presented to overcome challenges such as occlusion, clutter and similarly looking distractors. The problem has recently been addressed at the category level, where po

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RGB-D Sensors and Signal Processing for Fall Detectionis one of the most important application areas within the framework of Ambient-Assisted Living (AAL) solutions. Studies report that the majority of falls occur at home, as a person’s living environment is filled with potential hazards, predominantly in the living room and in the bedroom. In addition

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