Hole Filling Using Dominant Colour Plane for CNN-Based Stereo Matching

2022 ◽  
pp. 191-201
Author(s):  
Rachna Verma ◽  
Arvind Kumar Verma
Keyword(s):  
Stereo Matching ◽  
Hole Filling ◽  
Dominant Colour

scholarly journals Real Time Depth Hole Filling using Kinect Sensor and Depth Extract from Stereo Images

2019 ◽  
Vol 12 (Issue 3) ◽  
pp. 115-122
Author(s):  
Kapil Raviya ◽  
Ved Vyas Dwivedi ◽  
Ashish Kothari ◽  
Gunvantsinh Gohil
Keyword(s):  
Real Time ◽  
Stereo Matching ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Depth Map ◽  
Obstacle Detection ◽  
Block Matching ◽  
Microsoft Kinect ◽  
Hole Filling ◽  
Mathematical Algorithm

The researcher have suggested real time depth based on frequency domain hole filling. It get better quality of depth sequence generated by sensor. This method is capable to produce high feature depth video which can be quite useful in improving the performance of various applications of Microsoft Kinect such as obstacle detection and avoidance, facial tracking, gesture recognition, pose estimation and skeletal. For stereo matching approach images depth extraction is the hybrid (Combination of Morphological Operation) mathematical algorithm. There are few step like color conversion, block matching, guided filtering, minimum disparity assignment design, mathematical perimeter, zero depth assignment, combination of hole filling and permutation of morphological operator and last nonlinear spatial filtering. Our algorithm is produce smooth, reliable, noise less and efficient depth map. The evaluation parameter such as Structure Similarity Index Map (SSIM), Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) measure the results for proportional analysis.

Research on hole filling algorithm in triangle mesh models

2009 ◽  
Vol 29 (8) ◽  
pp. 2035-2037 ◽  
Author(s):  
Jian-lei TIAN ◽  
Xu-min LIU ◽  
Yong GUAN
Keyword(s):  
Triangle Mesh ◽  
Hole Filling ◽  
Mesh Models

Dense stereo matching by region growing based on disparity space sampling

2009 ◽  
Vol 29 (10) ◽  
pp. 2690-2692
Author(s):  
Bao-hai YANG ◽  
Xiao-li LIU ◽  
Dai-feng ZHA
Keyword(s):  
Stereo Matching ◽  
Region Growing ◽  
Dense Stereo Matching ◽  
Disparity Space

scholarly journals A Disparity Refinement Algorithm for Satellite Remote Sensing Images Based on Mean-Shift Plane Segmentation

2021 ◽  
Vol 13 (10) ◽  
pp. 1903
Author(s):  
Zhihui Li ◽  
Jiaxin Liu ◽  
Yang Yang ◽  
Jing Zhang
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Stereo Matching ◽  
Mean Shift ◽  
Segmentation Method ◽  
Remote Sensing Images ◽  
Edge Matching ◽  
Refinement Method ◽  
Initial Segmentation ◽  
Refinement Algorithm

Objects in satellite remote sensing image sequences often have large deformations, and the stereo matching of this kind of image is so difficult that the matching rate generally drops. A disparity refinement method is needed to correct and fill the disparity. A method for disparity refinement based on the results of plane segmentation is proposed in this paper. The plane segmentation algorithm includes two steps: Initial segmentation based on mean-shift and alpha-expansion-based energy minimization. According to the results of plane segmentation and fitting, the disparity is refined by filling missed matching regions and removing outliers. The experimental results showed that the proposed plane segmentation method could not only accurately fit the plane in the presence of noise but also approximate the surface by plane combination. After the proposed plane segmentation method was applied to the disparity refinement of remote sensing images, many missed matches were filled, and the elevation errors were reduced. This proved that the proposed algorithm was effective. For difficult evaluations resulting from significant variations in remote sensing images of different satellites, the edge matching rate and the edge matching map are proposed as new stereo matching evaluation and analysis tools. Experiment results showed that they were easy to use, intuitive, and effective.

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