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Structured Images for RGB-D Action Recognition

2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 2017
This paper presents an effective yet simple video representation for RGB-D based action recognition. It proposes to represent a depth map sequence into three pairs of structured dynamic images at body, part and joint levels respectively through bidirectional rank pooling.
Pichao Wang   +4 more
openaire   +1 more source

Accelerated DNA-SLAM for RGB-D images

Proceedings of the 2018 International Conference on Image and Graphics Processing, 2018
In the highly active research field of Simultaneous Localization And Mapping (SLAM), RGB-D images have been a major interest to use. Real-time SLAM for RGB-D images is of great importance since dense methods using all the depth and intensity values showed superior performance in the past.
Mina Ameli   +4 more
openaire   +2 more sources

Efficient image segmentation of RGB-D images

2017 12th International Conference on Computer Engineering and Systems (ICCES), 2017
Image segmentation is a fundamental problem in computer vision. With the current advent of depth sensors, it is gradually becoming a research focus on how to utilize the depth information to improve image segmentation. This paper proposes an automatic RGB-D image segmentation method in which the depth and RGB images are separately segmented and the ...
Islam I. Fouad   +2 more
openaire   +1 more source

3D Texture Recognition for RGB-D Images

2015
In this paper, we present a novel 3D object recognition system. In this system, we capture both the color and depth information of 3D objects using Kinect, and represent them in RGB-D images. To alleviate the deformations and partial defects of the obtained 3D surface textures, 3D texture reconstruction techniques are applied.
Guoqiang Zhong 0001   +3 more
openaire   +1 more source

Edge-Aware Convolution for RGB-D Image Segmentation

2020 35th International Conference on Image and Vision Computing New Zealand (IVCNZ), 2020
Convolutional Neural Networks using RGB-D images as input have shown superior performance in recent research in the field of semantic segmentation. In RGB-D data, the depth channel encodes information from the 3D spatial domain, which has an inherent difference with the color channels.
Rongsen Chen   +2 more
openaire   +1 more source

Compressive Temporal RGB-D Imaging

Imaging and Applied Optics 2017 (3D, AIO, COSI, IS, MATH, pcAOP), 2017
We report a compressive imaging system for high-speed color (RGB) video and range sensing based on the structured illumination. Random patterns are projected on the scene at a higher frame rate than that of the color camera. High-speed RGB-D scenes are reconstructed from a single 2D measurement via efficient algorithms.
Yuan, Xin, Sun, Yangyang, Pang, Shuo
openaire   +2 more sources

Hierarchical Image Segmentation Ensemble for Objectness in RGB-D Images

IEEE Transactions on Circuits and Systems for Video Technology, 2019
Objectness has recently become a standard step in many computer vision tasks. Among various techniques, those based on hierarchical image segmentation play a fundamental role for developments in new data modalities. In this paper, we address the problem of objectness in RGB-D images and propose a novel and effective approach, namely, hierarchical image
Huiqun Wang   +3 more
openaire   +1 more source

Thermal and RGB-D Imaging for Necrotizing Enterocolitis Detection

2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA), 2020
Necrotizing enterocolitis (NEC) is a severe condition in neonates, typically involving inflammation in the small intestine. In this paper, a novel automated image acquisition and analysis system combining an infrared thermal camera with a RGB-D sensor is proposed for detection of NEC in preterm newborns.
Yangyu Shi   +3 more
openaire   +2 more sources

Fine-Grained Categorization From RGB-D Images

IEEE Transactions on Multimedia, 2022
In the field of computer vision, fine-grained visual categorization has attracted a lot of attention and made great progress due to convolutional neural networks and a large number of publicly available datasets. With next-generation sensing technology, RGB-D cameras can provide high-quality synchronized RGB and depth images for solving many computer ...
Yanhao Tan   +5 more
openaire   +1 more source

A Study on OSAS Diagnostics Supported by RGB-D Imaging

2018 41st International Conference on Telecommunications and Signal Processing (TSP), 2018
The paper is a pilot study on OSAS diagnostics using automated measurement of cranio-facial features by RGB-D sensors. OSAS - obstructive sleep apnea syndrome - becomes very often phenomenon in respirology affecting the quality of life in each age.
Jozef Volák   +3 more
openaire   +2 more sources

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