Contributions to accurate and efficient cost aggregation for stereo matching

Dongming Chen 1
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : 3D-related applications are becoming more and more popular in our daily life, such as 3D movies, 3D printing, 3D maps, 3D object recognition, etc. Many applications require realistic 3D models and thus 3D reconstruction is a key technique behind them. In this thesis, we focus on a basic problem of 3D reconstruction, i.e. stereo matching, which searches for correspondences in a stereo pair or more images of a 3D scene. Although various stereo matching methods have been published in the past decades, it is still a challenging task since the high requirement of accuracy and efficiency in practical applications. For example, autonomous driving demands realtime stereo matching technique; while 3D object modeling demands high quality solution. This thesis is dedicated to develop efficient and accurate stereo matching method. The well-known bilateral filter based adaptive support weight method represents the state-of-the-art local method, but it hardly sorts the ambiguity induced by nearby pixels at different disparities but with similar colors. Therefore, we proposed a novel trilateral filter based method that remedies such ambiguities by introducing a boundary strength term. As evaluated on the commonly accepted Middlebury benchmark, the proposed method is proved to be the most accurate local stereo matching method at the time of submission (April 2013). The computational complexity of the trilateral filter based method is high and depends on the support window size. In order to enhance its computational efficiency, we proposed a recursive trilateral filter method, inspired by recursive filter. The raw costs are aggregated on a grid graph by four one-dimensional aggregations and its computational complexity proves to be O(N), which is independent of the support window size. The practical runtime of the proposed recursive trilateral filter based method processing 375 _ 450 resolution image is roughly 260ms on a PC with a 3:4 GHz Inter Core i7 CPU, which is hundreds times faster than the original trilateral filter based method. The trilateral filter based method introduced a boundary strength term, which is computed from color edges, to handle the ambiguity induced by nearby pixels at different disparities but with similar colors. The color edges consist of two types of edges, i.e. depth edges and texture edges. Actually, only depth edges are useful for the boundary strength term. Therefore, we presented a depth edge detection method, aiming to pick out depth edges and proposed a depth edge trilateral filter based method. Evaluation on Middlebury benchmark proves the effectiveness of the proposed depth edge trilateral filter method, which is more accurate than the original trilateral filter method and other local stereo matching methods.
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Submitted on : Monday, April 24, 2017 - 10:24:49 AM
Last modification on : Wednesday, November 20, 2019 - 2:55:53 AM


  • HAL Id : hal-01512628, version 1


Dongming Chen. Contributions to accurate and efficient cost aggregation for stereo matching. 2015. ⟨hal-01512628⟩



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