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Fast Depth Video Compression for Mobile RGB-D Sensors
IEEE Transactions on Circuits and Systems for Video Technology, 2016We propose a new method, called 3-D image warping-based depth video compression (IW-DVC), for fast and efficient compression of depth images captured by mobile RGB-D sensors. The emergence of low-cost RGB-D sensors has created opportunities to find new solutions for a number of computer vision and networked robotics problems, such as 3-D map building ...
Xiaoqin Wang +5 more
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Human pose estimation using two RGB-D sensors
2016 IEEE International Conference on Image Processing (ICIP), 2016Accurate human pose estimation plays an important role in various applications such as sports analysis, health care and gaming. Even though recent approaches have shown that 3D positions of body joints can be estimated from a single depth sensor, the depth data often suffer from sensing noise and self-occlusion.
Wanxin Xu +2 more
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Multi-Object Tracking based on RGB-D Sensors
Proceedings of the 2023 10th International Conference on Wireless Communication and Sensor Networks, 2023Keliang Zhu +5 more
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Unsupervised Depth Completion and Denoising for RGB-D Sensors
2022 International Conference on Robotics and Automation (ICRA), 2022Lei Fan 0005 +3 more
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RGB-D Sensors Extrinsic Calibration In Controlled Environment
2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 2021Krasimir Tonchev +3 more
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Sensor Evaluation for Voxel-Based RGB-D SLAM
2021 36th International Conference on Image and Vision Computing New Zealand (IVCNZ), 2021Joshua Clarke, Steven Mills
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Design and Control of an Aquatic Robot with RGB-D Sensor
2022 8th International Conference on Automation, Robotics and Applications (ICARA), 2022Madi Nurmanov +3 more
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Recognition and Location Algorithm for Pallets in Warehouses Using RGB-D Sensor
Applied Sciences (Switzerland), 2022Enli Lu, Huazhong Lu, Xingxing Zhou
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Instance segmentation of point cloud captured by RGB-D sensor based on deep learning
International Journal of Computer Integrated Manufacturing, 2021Jianzhong Fu
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