Abstract
In this paper, we introduce color segmentation based stereo correspondence for face images using wavelets. The intensity based correlation techniques are commonly employed to estimate the similarities between the stereo image pair, sensitive to shift variations and relatively lower performance in the featureless regions. Therefore, instead of pixel intensity, we consider wavelet coefficients of an approximation band, which is less sensitive to the shift variation. The approximation subband of reference image is segmented using mean shift segmentation method. A self-adapting dissimilarity measure that combines sum of absolute differences of wavelet coefficients and a gradient is employed to generate a disparity map of the stereo pairs. In our method instead of assigning a disparity value to a pixel, a disparity plane is assigned to each segment. Results show that the proposed technique produces smoother disparity maps with less computation cost.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Muhlmann K, Maier D, Hesser R, Manner R (2001) Calculating dense disparity maps from color stereo images, an efficient implementation. In: Proceedings of the IEEE workshop on stereo and multi-baseline vision (SMBV 2001), pp 30–36
Di Stefano L, Marchionni M, Mattoccia S, Neri G (2004) A fast area-based stereo matching algorithm. Image Vis Comput 22:983–1005
Yoon KJ, Kweon IS (2006) Adaptive support-weight approach for correspondence search. IEEE Trans Pattern Anal Mach Intell 28:650–656
Seok Y, Lee S (2011) Robust stereo matching using adaptive normalized cross correlation. IEEE Trans PAMI 33(4):807–822
Hamzah R, Hamid A, Md. Salim S (2010) The solution of stereo correspondence problem using block matching algorithm in stereo vision mobile robot. IICRD, pp 733–737
Bobick AF, Intille SS (1999) Large occlusion stereo. Int J Comput Vis 33(3):181–200
Kang SB, Szeliski R, Jinxjang C (2001) Handling occlusions in dense multi-view stereo. Proceedings of the IEEE conference computer vision and pattern recognition, vol 1, pp 103–110
Kim H, Yang S, Sohn K (2003) 3D reconstruction of stereo images for interaction between real and virtual worlds. In: Proceedings of the IEEE international conference on mixed and augmented reality
Ogale AS, Aloimonos Y (2008) Robust contrast invariant stereo correspondence. Proceedings of the IEEE international conference on robotics and automation, ICRA 2005, pp 819–824
Bleyer M, Gelautz M (2005) A layered stereo matching algorithm using image segmentation and global visibility constraints. ISPRS J Photogramm Remote Sens 59(3):128–150
Bleyer M, Gelautz M (2005) Graph-based surface reconstruction from stereo pairs using image segmentation. In: SPIE, vol 5665, pp 288–299
Deng Y, Yang Q, Lin X, Tang X (2005) A symmetric patch-based correspondence model for occlusion handling. In: ICCV, pp II:1316–1322
Hong L, Chen G (2004) Segment-based stereo matching using graph cuts. In: CVPR, vol I, pp 74–81
Xiao J, Xia L, Lin L (2010) A segment based stereo matching method with ground control points. In: IEEE transaction on ESIAT
Mallat S (1999) A wavelet tour of signal processing. Academic Press, New York
Sarkar I, Bansal M (2007) A wavelet-based multiresolution approach to solve the stereo correspondence problem using mutual information. IEEE Trans Syst Man Cybern 37:1009–1014
Begheri P, Sedan CV (2010) Stereo correspondence matching using multiwavelets. In: Fifth international conference on digital telecommunication
Bhatti A, nahavandi S, Hossny M (2010) Wavelets/Multiwavelets bases and correspondence estimation problem; an analytic study. In: 11th international conference on control, automation, robotics and vision
Klaus A, Sormann M, Karner K (2006) Segment-based stereo matching using belief propagation and a self-adapting dissimilarity measure. In: Proceeding of the ICPR
Comaniciu D, Meer P (2002) Mean shift a robust approach toward feature space analysis. IEEE PAMI 24:603–619
Fusiello A, Irsara L (2008) Quasi-euclidean uncalibrated epipolar rectification. In: ICPR, pp 1–4
Middlebury database (2010) http://vision.middlebury.edu/stereo/data/
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer India
About this paper
Cite this paper
Prabhakar, C.J., Jyothi, K. (2013). Segment-Based Stereo Correspondence of Face Images Using Wavelets. In: S, M., Kumar, S. (eds) Proceedings of the Fourth International Conference on Signal and Image Processing 2012 (ICSIP 2012). Lecture Notes in Electrical Engineering, vol 222. Springer, India. https://doi.org/10.1007/978-81-322-1000-9_8
Download citation
DOI: https://doi.org/10.1007/978-81-322-1000-9_8
Published:
Publisher Name: Springer, India
Print ISBN: 978-81-322-0999-7
Online ISBN: 978-81-322-1000-9
eBook Packages: EngineeringEngineering (R0)