Results 261 to 270 of about 16,759,811 (301)

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, Oliver Wasenmüller, Mohammad Reza Soheili, Jamshid Shanbehzadeh, Didier Stricker   +4 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, Mohammad Muntasir Rahman, Yanfu Yan, Jian Xue 0002, Ling Shao 0001, Ke Lu 0002   +5 more
openaire   +1 more source

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, Sherine Rady, Mostafa G. M. Mostafa   +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, Xin Mao, Yaxin Shi, Junyu Dong   +3 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

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, Pierre Payeur, Monique Frize, Erika Bariciak   +3 more
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, Di Huang 0001, Kui Jia, Yunhong Wang 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, Fang-Lue Zhang, Taehyun Rhee   +2 more
openaire   +1 more source

Domain adaptation from RGB-D to RGB images

Signal Processing, 2017
The 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, Min Fang, Jujie Zhang, Jinqiao Wu 0001   +3 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, Dusan Koniar, Frantisek Jabloncík, Libor Hargas   +3 more
openaire   +2 more sources