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Shadow Removal from Single RGB-D Images
2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014We present the first automatic method to remove shadows from single RGB-D images. Using normal cues directly derived from depth, we can remove hard and soft shadows while preserving surface texture and shading. Our key assumption is: pixels with similar normals, spatial locations and chromaticity should have similar colors. A modified nonlocal matching
Yao Xiao +2 more
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From RGB-D Images to RGB Images
ACM Transactions on Intelligent Systems and Technology, 2015Mining object-level knowledge, that is, building a comprehensive category model base, from a large set of cluttered scenes presents a considerable challenge to the field of artificial intelligence. How to initiate model learning with the least human supervision (i.e., manual labeling) and how to encode the structural knowledge are two elements of this ...
Quanshi Zhang +4 more
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Domain adaptation from RGB-D to RGB images
Signal Processing, 2017The introduction of depth cameras offers an opportunity to utilize the depth images to help the object recognition tasks. However, when our target tasks are classifying RGB images, how can we use the RGB-D images? To deal with this problem, we proposed a novel domain adaptation method by learning from RGB-D images in source domain to recognize RGB ...
Xiao Li 0008 +3 more
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Shading-Based Shape Refinement of RGB-D Images
2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013We present a shading-based shape refinement algorithm which uses a noisy, incomplete depth map from Kinect to help resolve ambiguities in shape-from-shading. In our framework, the partial depth information is used to overcome bas-relief ambiguity in normals estimation, as well as to assist in recovering relative albedos, which are needed to reliably ...
Lap-Fai Yu +3 more
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Indoor human detection using RGB-D images
2016 IEEE International Conference on Information and Automation (ICIA), 2016Recently, RGB-D sensors such as Kinect and Xtion have received considerable attention since they provide depth image that is robust to light variation in the environment. They are mainly used for human computer interaction, surveillance and so on. In this paper, we concentrate on indoor human detection using RGB-D images.
Baopu Li +4 more
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Segmentation of Shipping Bags in RGB-D Images
2022 IEEE 5th International Conference on Image Processing Applications and Systems (IPAS), 2022Elena Vasileva, Zoran A. Ivanovski
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Point-Based Object Recognition in RGB-D Images
2015To operate autonomously a robot system needs among others to perceive the environment and to recognize the scene objects. In particular, nowadays an RGB-D sensor can be applied for vision-based perception. In this paper, two data-driven RGB-D image analysis steps, required for a reliable 3D object recognition process, are studied and appropriate ...
Artur Wilkowski +2 more
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RGB-T image analysis technology and application: A survey
Engineering Applications of Artificial Intelligence, 2023Yunhui Yan +2 more
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Glass Segmentation With RGB-Thermal Image Pairs
IEEE Transactions on Image Processing, 2023Jian Wang, Dong Huo
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Review on RGB-D Image Classification
Laser & Optoelectronics Progress, 2016涂淑琴 Tu Shuqin +4 more
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