Results 21 to 30 of about 78,230 (294)
Revista Politécnica, 2019 RGB-D sensors have allowed attacking many classical problems in computer vision such as segmentation, scene representations and human interaction, among many others.
Fabián Castillo +2 more
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SCENE SEMANTIC SEGMENTATION FROM INDOOR RGB-D IMAGES USING ENCODE-DECODER FULLY CONVOLUTIONAL NETWORKS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 With increasing attention for the indoor environment and the development of low-cost RGB-D sensors, indoor RGB-D images are easily acquired. However, scene semantic segmentation is still an open area, which restricts indoor applications.
Z. Wang, T. Li, L. Pan, Z. Kang
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People detection in RGB-D Data [PDF]
2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011 People detection is a key issue for robots and intelligent systems sharing a space with people. Previous works have used cameras and 2D or 3D range finders for this task. In this paper, we present a novel people detection approach for RGB-D data. We take inspiration from the Histogram of Oriented Gradients (HOG) detector to design a robust method to ...
Luciano Spinello, Kai O. Arras
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AN RGB-D DATA PROCESSING FRAMEWORK BASED ON ENVIRONMENT CONSTRAINTS FOR MAPPING INDOOR ENVIRONMENTS [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 The adoption of RGB and depth (RGB-D) sensors for surveying applications (i.e., building information modeling [BIM], indoor navigation, and three-dimensional [3D] models) to replace expensive and time-consuming methods (e.g., stereo cameras, laser ...
W. Darwish +5 more
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A Primal-Dual Framework for Real-Time Dense RGB-D Scene Flow [PDF]
, 2015 This paper presents the first method to compute dense scene flow in real-time for RGB-D cameras. It is based on a variational formulation where brightness constancy and geometric consistency are imposed.
Cremers, Daniel +3 more
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Unsupervised Learning of Long-Term Motion Dynamics for Videos [PDF]
, 2017 We present an unsupervised representation learning approach that compactly encodes the motion dependencies in videos. Given a pair of images from a video clip, our framework learns to predict the long-term 3D motions.
Alahi, Alexandre +4 more
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Efficient RGB–D data processing for feature–based self–localization of mobile robots
International Journal of Applied Mathematics and Computer Science, 2016 The problem of position and orientation estimation for an active vision sensor that moves with respect to the full six degrees of freedom is considered. The proposed approach is based on point features extracted from RGB-D data.
Kraft Marek +4 more
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Adversarial Texture Optimization From RGB-D Scans [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 Realistic color texture generation is an important step in RGB-D surface reconstruction, but remains challenging in practice due to inaccuracies in reconstructed geometry, misaligned camera poses, and view-dependent imaging artifacts. In this work, we present a novel approach for color texture generation using a conditional adversarial loss obtained ...
Huang, Jingwei +7 more
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Depth Super-Resolution Meets Uncalibrated Photometric Stereo [PDF]
, 2017 A novel depth super-resolution approach for RGB-D sensors is presented. It disambiguates depth super-resolution through high-resolution photometric clues and, symmetrically, it disambiguates uncalibrated photometric stereo through low-resolution depth ...
Cremers, Daniel +3 more
core +2 more sources
IEEE Access, 2022 The RGB-D-based human action recognition is gaining increasing attention because the different modalities can provide complementary information. However, the recognition performance is still not satisfactory due to the limited ability to learn spatial ...
Qin Cheng +4 more
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