스테레오 비전에서 비용 축적 알고리즘의 비교 분석 = Comparative Analysis of Cost Aggregation Algorithms in Stereo Vision

다국어 초록 (Multilingual Abstract)

Human visual system infers 3D vision through stereo disparity in the stereoscopic images, and stereo visioning are recently being used in consumer electronics which has resulted in much research in the application field. Basically, stereo vision system consists of four processes, which are cost computation, cost aggregation, disparity calculation, and disparity refinement. In this paper, we present and evaluate the existing various methods, focusing on cost aggregation for stereo vision system to comparatively analyze the performance of their algorithms for a given set of resources. Experiments show that Normalized Cross Correlation and Zero-Mean Normalized Cross Correlation provide higher accuracy, however they are computationally heavy for embedded system in the real time systems. Sum of Absolute Difference and Sum of Squared Difference are more suitable selection for embedded system, but they should be required on improvement to apply to the real world system.

참고문헌 (Reference)

1 김영섭, "깊이맵 향상을 위한 전처리 과정과 그래프 컷에 관한 연구" 한국반도체디스플레이기술학회 10 (10): 99-103, 2011

2 Jenny C. A. Read, "What is stereoscopic vision good for" 9391 : 2015

3 Martin S. Banks, "Stereoscopy and the Human Visual System" 12 (12): 2012

4 Alberto Apostolico, "Pattern Matching Algorithms" Oxford University Press 1997

5 Y. M. Fouda, "One-Dimensional Vector based Pattern Matching" 2014

6 Nadia Baha, "Neural Disparity Map Estimation from Stereo Image" 9 (9): 2012

7 Dongbo Min, "Joint Histogram based Cost Aggregation for Stereo Matching" 35 (35): 2013

8 Heiko Hirschmuller, "Evaluation of Stereo Matching Costs on Images with Radiometric Differences" 31 (31): 2008

9 Stephan Reichelt, "Depth Cues in Human Visual Perception and their Realization in 3D Displays" 7690 : 2010

10 Federico Tombari, "Classification and Evaluation of Cost Aggregation Methods for Stereo Correspondence" 2008

11 Karsten Muhlmann, "Calculating dense disparity maps from color stereo images, an efficient implementation" 2001

12 Myron Z. Brown, "Advances in Computational Stereo" 25 (25): 2003

13 Daniel Scharstein, "A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms" 47 (47): 2002

14 D. Wang, "A Joint Image Quality Assessment Method based on Global Phase Coherence and Structural Similarity" 2010