Generating an accurate and dense disparity image is one of the important requirements for many applications such as 3D video and stereo vision-based advanced driver assistance systems (ADAS). Depth estimation is the process of obtaining a depth map based on two or more reference images. Recently, several techniques that use semi-global optimization for estimating depth maps have been suggested. Although robustness against illumination changes is a vital factor in applications like ADAS, semi-global matching (SGM) based on mutual information achieves limited performance under illumination changes. In this paper, a modified SGM algorithm is proposed which is based on adaptive window patterns of census transform. The goal of the proposed method is to improve the quality of the estimated depth map while reducing the processing time and making it applicable for depth-based pedestrian detection techniques. To enhance the quality of the estimated depth map, a spatial Gaussian weighted averaging filter along with a color-aware filter is implemented. To demonstrate the efficiency of the proposed method, the Middlebury stereo dataset and the KITTI vision benchmark have been used on the experiments. Experimental results show that the proposed method reduces the percentage of bad pixels by 0.7–1.2% for the test sequences compared to the original SGM algorithm with reduced processing time.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    SGM-based dense disparity estimation using adaptive Census transform


    Beteiligte:
    Loghman, Maziar (Autor:in) / Kim, Joohee (Autor:in)


    Erscheinungsdatum :

    01.12.2013


    Format / Umfang :

    2990117 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Three-view dense disparity estimation with occlusion detection

    Xiaodong Huang, / Dubois, E. | IEEE | 2005


    Dense Motion and Disparity Estimation Via Loopy Belief Propagation

    Isard, M. / MacCormick, J. | British Library Conference Proceedings | 2006


    Stereo image reconstruction using regularized adaptive disparity estimation

    Bae, K.-H. / Ko, J.-H. / Lee, J.-S. | British Library Online Contents | 2007


    An Improved Algorithm for Dense Disparity Estimation on Aerial Images

    Chung, K. L. / Hwang, M. H. / Chen, C. S. | British Library Online Contents | 2002


    Errata: Stereo image reconstruction using regularized adaptive disparity estimation

    Bae, K.-H. / Ko, J.-H. / Lee, J.-S. | British Library Online Contents | 2008