Real Time Depth Hole Filling using Kinect Sensor and Depth Extract from Stereo Images-Reference-Cited by-同舟云学术

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

Published:2019-10-01 Issue:Issue 3 Volume:12 Page:115-122
ISSN:2320-8481
Container-title:Oriental journal of computer science and technology
language:en
Short-container-title:Orient. J. Comp. Sci. and Technol

Author:

Raviya Kapil¹^ORCID,Dwivedi Ved Vyas²,Kothari Ashish³,Gohil Gunvantsinh⁴

Affiliation:

1. College of Agricultural Engineering and Technology, Electronics Communication Engineering, Junagadh Agricultural University, Gujarat, India

2. C. U. Shah University, Pro- Vice Chancellor, Wadhwan City, Gujarat, India

3. Electronics Communication Engineering, Atmiya Institute of technology and Science, Gujarat technological university, Gujarat, India

4. College of Agricultural Engineering and Technology, Junagadh Agricultural University, Gujarat, India

Abstract

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.

Publisher

Oriental Scientific Publishing Company

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference15 articles.

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3. He, K., Sun, J. and Tang, X., 2010, September. Guided image filtering. In European conference on computer vision (pp. 1-14). Springer Berlin Heidelberg.

4. K. Rao, Joohee Kim, “Refinement of Depth Maps Generated By Low-Cost Depth Sensors,” 978-1-4673-2990-3, pp. 355-358, ISOCC, IEEE, 2012.

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