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Efficient foreground extraction using RGB-D imaging
Multimedia Tools and Applications, 2013Image segmentation is one of the most important topics in the field of computer vision. As a result, many image segmentation approaches have been proposed, and interactive methods based on energy minimization such as GrabCut, have shown successful results.
Sang-Wook Lee +2 more
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Scale adaptive supervoxel segmentation of RGB-D image
2016 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2016Superpixels are perceptually meaningful atomic regions that can effectively capture image features. We propose a novel scale adaptive supervoxel segmentation algorithm for RGB-D images, i.e., small supervoxels in content-dense regions (e.g., with high intensity or color variation) and large supervoxels in content-sparse regions.
Peng Xu, Jie Li 0040, Juan Yue, Xia Yuan
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An approach to loop-closing based on RGB-D images
2013 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2013To solve the problem of accuracy and robustness seriously affected by the external environment when loop-closing using vision for mobile robot, a method based on RGB-D image for loop-closing detection is proposed. The front area contour which will be used for contour matching is extracted from the depth information.
Fengda Zhao +3 more
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A Robust RGB-D Image-Based SLAM System
2017Visual SLAM is widely used in robotics and computer vision. Although there have been many excellent achievements over the past few decades, there are still some challenges. 2D feature-based SLAM algorithm has been suffering from the inaccurate or insufficient correspondences while dealing with the case of textureless or frequently repeating regions ...
Liangliang Pan +3 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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