Superpixel-based depth map enhancement and hole filling for view interpolation

2017 ◽  
Author(s):  
Xiaohui Yang ◽  
Zhiquan Feng ◽  
Tao Xu ◽  
Yan Jiang ◽  
Haokui Tang
Keyword(s):  
Depth Map ◽  
Hole Filling ◽  
View Interpolation

Depth Map Driven Hole Filling Algorithm Exploiting Temporal Correlation Information

2014 ◽  
Vol 60 (2) ◽  
pp. 394-404 ◽  
Author(s):  
Chao Yao ◽  
Tammam Tillo ◽  
Yao Zhao ◽  
Jimin Xiao ◽  
Huihui Bai ◽  
...  
Keyword(s):  
Depth Map ◽  
Temporal Correlation ◽  
Hole Filling ◽  
Correlation Information

scholarly journals Real-time RGB-D image stitching using multiple Kinects for improved field of view

2017 ◽  
Vol 14 (2) ◽  
pp. 172988141769556 ◽  
Author(s):  
Hengyu Li ◽  
Hang Liu ◽  
Ning Cao ◽  
Yan Peng ◽  
Shaorong Xie ◽  
...  
Keyword(s):  
Real Time ◽  
Anisotropic Diffusion ◽  
Color Image ◽  
Depth Map ◽  
Color Images ◽  
Field Of View ◽  
Hole Filling ◽  
Depth Data ◽  
Registration Data ◽  
Filling Method

This article concerns the problems of a defective depth map and limited field of view of Kinect-style RGB-D sensors. An anisotropic diffusion based hole-filling method is proposed to recover invalid depth data in the depth map. The field of view of the Kinect-style RGB-D sensor is extended by stitching depth and color images from several RGB-D sensors. By aligning the depth map with the color image, the registration data calculated by registering color images can be used to stitch depth and color images into a depth and color panoramic image concurrently in real time. Experiments show that the proposed stitching method can generate a RGB-D panorama with no invalid depth data and little distortion in real time and can be extended to incorporate more RGB-D sensors to construct even a 360° field of view panoramic RGB-D image.

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.

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