Results 21 to 30 of about 25,036,571 (294)

ENHANCED RGB-D MAPPING METHOD FOR DETAILED 3D MODELING OF LARGE INDOOR ENVIRONMENTS [PDF]

open access: yesISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
RGB-D sensors are novel sensing systems that capture RGB images along with pixel-wise depth information. Although they are widely used in various applications, RGB-D sensors have significant drawbacks with respect to 3D dense mapping of indoor ...
S. Tang   +6 more
doaj   +1 more source

Two-Stream RGB-D Human Detection Algorithm Based on RFB Network

open access: yesIEEE Access, 2020
In order to effectively combine RGB image features with depth image features for human detection, this paper proposes a two-stream RGB-D human detection algorithm based on RFB network. The proposed algorithm mainly contains three parts: RGB-stream, Depth-
Wenli Zhang   +4 more
doaj   +1 more source

Pedestrian localization using RGB-D camera.

open access: yes, 2021
Left: Two pedestrians detected in the RGB image of the robot’s RGB-D camera with the bounding box centroids marked in pink and green. Right: The same bounding boxes superimposed over the depth image from the RGB-D camera.
Moumita Paul (11777681)   +4 more
core   +1 more source

Method for RGB-D image segmentation

open access: yes, 2022
The invention discloses a method for RGB-D image segmentation, which is based on the fact that the method carries out semantic level segmentation on an RGB-D color depth image, extracts foreground pixel information in the depth image and takes a weight ...
Xu, Zhijie   +5 more
core   +2 more sources

A Novel Semantic Segmentation Algorithm for RGB-D Images Based on Non-Symmetry and Anti-Packing Pattern Representation Model

open access: yesIEEE Access, 2023
With the rapid development of deep learning technology, the accuracy of image semantic segmentation tasks has been greatly improved. However, indoor RGB-D semantic segmentation remains a challenging problem because of the complexity of indoor ...
Yunping Zheng   +5 more
doaj   +1 more source

RGB-D datasets using microsoft kinect or similar sensors: a survey [PDF]

open access: yes, 2016
RGB-D data has turned out to be a very useful representation of an indoor scene for solving fundamental computer vision problems. It takes the advantages of the color image that provides appearance information of an object and also the depth image that ...
Cai, Ziyun   +7 more
core   +2 more sources

SCENE SEMANTIC SEGMENTATION FROM INDOOR RGB-D IMAGES USING ENCODE-DECODER FULLY CONVOLUTIONAL NETWORKS [PDF]

open access: yesThe 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
doaj   +1 more source

Fast Edge Detection in RGB-D Images [PDF]

open access: yes, 2014
The understanding of scenes is a key aspect of computer vision. Edge detection helps us to understand more about the scene structure since the edges mark a clear distinction for a transition from one region with similar properties to another one. When the edges are obtained from changes in orientation, we can use them to find key planes and describe ...
Heriberto Casarrubias-Vargas   +2 more
openaire   +1 more source

Structure-Preserving Binary Representations for RGB-D Action Recognition [PDF]

open access: yes, 2015
In this paper, we propose a novel binary local representation for RGB-D video data fusion with a structure-preserving projection. Our contribution consists of two aspects.
Liu, Li, Shao, Ling, Yu, Mengyang
core   +1 more source

Reflectance map for respective bands and RGB image of the plots, (a) Blue, (b) Green, (c) NIR, (d) Red-edge, (e) Red, and (f) RGB image.

open access: yes, 2023
Reflectance map for respective bands and RGB image of the plots, (a) Blue, (b) Green, (c) NIR, (d) Red-edge, (e) Red, and (f) RGB image.
Michael L. Flessner (15332778)   +5 more
core   +1 more source

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