Paper Info
Title
Efficient Depth Map Estimation Method Based On Gradient Weight Cost Aggregation Strategy
Abstract
A cross-based framework strategy for performance of gradient-based weight cost aggregation strategy is presented. We formulate the process as a local regression problem consisting of two main steps. The first step is to calculate estimates for a set of points within a shape-adaptive local support region. The second step is to aggregate the matching cost for the gradient-based weight of the support region at the outmost pixel. The proposed algorithm achieves strong results in an efficient manner using the two main steps. W e have achieved improvement of up to 6.9%, 8.4% and 8.3%, when compared with Adaptive Support weight (ASW) algorithm. Comparing to Cross-based algorithm, the proposed algorithm gives 2.0%, 1.3% and 1.0% in terms of non-occlusion, all and discontinuities, respectively.
Year
DOI
Venue
2013
10.1109/VCIP.2013.6706337
2013 IEEE INTERNATIONAL CONFERENCE ON VISUAL COMMUNICATIONS AND IMAGE PROCESSING (IEEE VCIP 2013)
Keywords
Field
DocType
depth map estimation, aggregation, gradient-based weight, matching cost, support region
Computer vision,Classification of discontinuities,Pattern recognition,Regression analysis,Image matching,Computer science,Local regression,Artificial intelligence,Pixel,Cost aggregation,Depth map
Conference
Citations 
PageRank 
References 
0
0.34
6
Authors
4
Name
Order
Citations
PageRank
Gwang-Soo Hong1215.53
Byung-Gyu Kim239639.17
Taejung Kim316917.76
Jeongju Yu400.68