Manuscript Number : IJSRSET207261
Review on Stereo Vision Based Depth Estimation
Authors(3) :-Sheshang Degadwala, Dhairya Vyas, Arpana Mahajan
Stereo vision is a challenging problem and it is a wide research topic in computer vision. It has got a lot of attraction because it is a cost efficient way in place of using costly sensors. Stereo vision has found a great importance in many fields and applications in today’s world. Some of the applications include robotics, 3-D scanning, 3-D reconstruction, driver assistance systems, forensics, 3-D tracking etc. The fundamental test of sound system vision is to create exact difference map. Sound system vision calculations for the most part perform four stages: first, coordinating cost calculation; second, cost collection; third, dissimilarity calculation or enhancement; and fourth, divergence refinement. Sound system coordinating issues are likewise examined. An enormous number of calculations have been produced for sound system vision. But characterization of their performance has achieved less attraction. This paper gives a brief overview of the existing stereo vision algorithms. After evaluating the papers we can say that focus has been on cost aggregation and multi-step refinement process. Segment-based methods have also attracted attention due to their good performance. Also, using improved filter for cost aggregation in stereo matching achieves better results.
Sheshang Degadwala
Stereo vision, Disparity map, matching cost computation, cost aggregation, disparity computation, disparity optimization, disparity refinement, segment-based method, stereo matching.
Publication Details
Published in :
Volume 6 | Issue 2 | March-April 2019 Article Preview
Head of Computer Engineering Department, Sigma Institute of Engineering, Vadodara, Gujarat, India
Dhairya Vyas
Managing Director, Shree Drashti Infotech LLP, Vadodara, Gujarat, India
Arpana Mahajan
Assistant Professor, Computer Engineering Department, Sigma Institute of Engineering, Vadodara, Gujarat, India
Date of Publication :
2019-04-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) :
665-671
Manuscript Number :
IJSRSET207261
Publisher : Technoscience Academy
Journal URL :
https://ijsrset.com/IJSRSET207261