A Convex Optimization Approach for Depth Estimation Under Illumination Variation

Miled, Wided; Pesquet, J.-C.; Parent, Michel

doi:10.1109/tip.2008.2011386

Cited by 40 publications

(31 citation statements)

References 60 publications

(89 reference statements)

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“…Miled et al [19] developed a spatially varying multiplicative model to account for brightness changes induced between left and right views. The depth estimation problem is then formulated as a constrained optimization problem in which an appropriate convex objective function is minimized under various convex constraints modelling prior knowledge and observed information.…”

Section: : Refines Disparity B : Aggregates Cost a : Computes Matchmentioning

confidence: 99%

Visual stereo matching combined with intuitive transition of pixel values

Shin

Kim

Chung

2015

Multimed Tools Appl

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The objective of stereo matching is to find the corresponding pixels from similar two or more images. However, it is difficult problem to get precise and consistent disparity under a variety of real world situations. In other words, the color values of stereo images are easily influenced by radiometric factors such as illumination direction, illumination color, and camera exposure. Therefore, conventional stereo matching methods can have low performances under radiometric conditions. In this paper, we propose a novel stereo matching approach that is robust in controlling various radiometric variations such as local and global radiometric variations. We designed a hybrid stereo matching approach using transition of pixel values and data fitting. Transition of pixel values is utilized for the coarse stereo matching stage, and polynomial curve fitting is used for the fine stereo matching stage. Experimental results show that the proposed method has better performances compared to the stereo matching algorithms of comparison group under severely different radiometric conditions between stereo images. Consequentially, we demonstrate that the proposed method is less sensitive to various radiometric variations, and shows an outstanding performance in computational complexity.

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Section: : Refines Disparity B : Aggregates Cost a : Computes Matchmentioning

confidence: 99%

Visual stereo matching combined with intuitive transition of pixel values

Shin

Kim

Chung

2015

Multimed Tools Appl

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“…The method presented in (Malik and Choi, 2008) is based in the shape from focus approach and use a defocus measure based in an optic transfer function implemented in the Fourier domain. In (Miled & Pesquet, 2009), the authors present a novel method based on stereo that help to estimate depth maps of scene that are subject to changes www.intechopen.com in illumination. Other works propose to combine different methods to obtain the range maps.…”

Section: Related Workmentioning

confidence: 99%

Multisensorial Active Perception for Indoor Environment Modeling

Torres-Méndez¹

2010

Sensor Fusion and Its Applications

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“…. , M }, in a Hilbert image space H. The intersection S of all the M sets (Sm) 1≤m≤M constitutes the family of possible solutions [15,16]. Therefore, it is enough to find an acceptable solution in S which minimizes the underlying objective function J:…”

Section: Retained Dde Proceduresmentioning

confidence: 99%

“…However, the classical block-based technique does not always guarantee a consistent disparity map. In this paper, we propose to perform the joint coding of the stereo pair using the VLS developed in [12] along with the Dense DE (DDE) method described in [15,16]. We have retained such DE method because it achieves good results compared with the state-ofthe-art methods, such as dynamic programming [17] and graph cuts [18].…”

Section: Introductionmentioning

confidence: 99%

Dense disparity map representations for stereo image coding

Kaaniche

Miled

Pesquet‐Popescu

et al. 2009

2009 16th IEEE International Conference on Image Processing (ICIP)

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Marne-la-Vallée, France pesquet@univ-mlv.fr ABSTRACTResearch in stereo image coding has focused on the disparity estimation/compensation process to exploit the cross-view redundancies.Most of the reported methods use a classical block-based technique in order to estimate the disparity field. However, this estimation technique does not always provide an accurate disparity map, which may affect the disparity compensation step. In this paper, we propose to use an estimation method that produces a dense and smooth disparity map. Then, on the one hand, this map is segmented and efficiently coded by exploiting the high correlation between neighboring disparity values. On the other hand, we integrate the disparity information into a vector lifting scheme for stereo image coding. Experimental results indicate that the proposed coding scheme outperforms the conventional methods employing a block-based disparity estimation.Index Terms-disparity estimation, dense disparity map, stereoscopic image coding, vector lifting scheme.

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A Convex Optimization Approach for Depth Estimation Under Illumination Variation

Cited by 40 publications

References 60 publications

Visual stereo matching combined with intuitive transition of pixel values

Visual stereo matching combined with intuitive transition of pixel values

Multisensorial Active Perception for Indoor Environment Modeling

Dense disparity map representations for stereo image coding

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