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Large-area depth recovery for RGB-D camera
2015 IEEE International Conference on Image Processing (ICIP), 2015In this paper, a large-area depth recovery method for RGB-D camera is proposed. Considering that pixels along edges between different regions usually share similar depth values, we first select reliable pixels along edges of large-area depth missing regions and project them into the world coordinate system.
Zengqiang Yan, Li Yu 0003, Zixiang Xiong
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Semi-direct Tracking and Mapping with RGB-D Camera
2019In this paper we present a novel semi-direct tracking and mapping approach for RGB-D cameras, which inherits the advantages of both direct and feature-based methods, and achieves high accuracy and robustness. The proposed method comprises three threads: tracking, local mapping and loop closing. In the tracking thread, the input RGB-D frames are tracked
Ke Liu +4 more
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Fall Recovery Subactivity Recognition With RGB-D Cameras
IEEE Transactions on Industrial Informatics, 2016Accidental falls have been identified as a cause of mortality for elders who live alone around the globe. Following a fall, additional injury can be sustained if proper fall recovery techniques are not followed. These secondary complications can be reduced if the person had access to safe recovery procedures or were assisted, either by a person or a ...
Kalana Ishara Withanage +4 more
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Semantic Object and Plane SLAM for RGB-D Cameras
2019Simultaneous Localization And Mapping (SLAM) is a fundamental problem in mobile robotics as well as in virtual reality (VR) and augmented reality (AR). Traditional visual-SLAM systems, such as ORB-SLAM, deal with sparse features extracted from high gradient image regions.
Longyu Zheng, Wenbing Tao
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Dense Frame-to-Model SLAM with an RGB-D Camera
2018In this paper, a dense frame-to-model Simultaneous Localization And Mapping (SLAM) with an RGB-D camera is proposed, which achieves a more accurate trajectory in contrast to traditional frame-to-model methods. In the frontend, dense photometric information and geometric information are combined to perform a more robust tracking.
Xiaodan Ye +4 more
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Visual Camera Re-Localization from RGB and RGB-D Images Using DSAC
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021Carsten Rother, Eric Brachmann
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Calibrating Non-overlapping RGB-D Cameras
2014 22nd International Conference on Pattern Recognition, 2014Wuhe Zou, Shigang Li 0001
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In-field tea shoot detection and 3D localization using an RGB-D camera
Computers and Electronics in Agriculture, 2021Jianneng Chen +2 more
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Can ADAS Distract Driver’s Attention? An RGB-D Camera and Deep Learning-Based Analysis
Applied Sciences (Switzerland), 2021Sandro Moos +2 more
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