Title
Real-time stereo using approximated joint bilateral filtering and dynamic programming
Abstract
We present a stereo algorithm that is capable of estimating scene depth information with high accuracy and in real time. The key idea is to employ an adaptive cost-volume filtering stage in a dynamic programming optimization framework. The per-pixel matching costs are aggregated via a separable implementation of the bilateral filtering technique. Our separable approximation offers comparable edge-preserving filtering capability and leads to a significant reduction in computational complexity compared to the traditional 2D filter. This cost aggregation step resolves the disparity inconsistency between scanlines, which are the typical problem for conventional dynamic programming based stereo approaches. Our algorithm is driven by two design goals: real-time performance and high accuracy depth estimation. For computational efficiency, we utilize the vector processing capability and parallelism in commodity graphics hardware to speed up this aggregation process over two orders of magnitude. Over 90 million disparity evaluations per second [the number of disparity evaluations per seconds (MDE/s) corresponds to the product of the number of pixels and the disparity range and the obtained frame rate and, therefore, captures the performance of a stereo algorithm in a single number] are achieved in our current implementation. In terms of quality, quantitative evaluation using data sets with ground truth disparities shows that our approach is one of the state-of-the-art real-time stereo algorithms.
Year
DOI
Venue
2014
10.1007/s11554-012-0275-4
Journal of Real-Time Image Processing
Keywords
Field
DocType
Real-time stereo, Cost aggregation, Bilateral filtering, Dynamic programming, Disparity map, Stereo video
Computer vision,Dynamic programming,Graphics hardware,Computer science,Filter (signal processing),Real-time computing,Ground truth,Frame rate,Artificial intelligence,Bilateral filter,Speedup,Computational complexity theory
Journal
Volume
Issue
ISSN
9
3
1861-8219
Citations 
PageRank 
References 
4
0.41
44
Authors
4
Name
Order
Citations
PageRank
Liang Wang11567158.46
Ruigang Yang23675226.03
Minglun Gong3134085.53
Miao Liao441820.41