IJSER Home >> Journal >> IJSER
International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 12    
Website: http://www.ijser.org
scirp IJSER >> Volume 2, Issue 12, December 2011
Collision-Free Navigation for Blind Persons using Stereo Matching
Full Text(PDF, 3000)  PP.  
Author(s)
Saeid Fazli, Hajar Mohammadi D
KEYWORDS
Obstacle detection, stereo matching, negative obstacle, positive obstacle, blind navigation, visually impaired
ABSTRACT
A blind person in an urban environment has to navigate around obstacles and hazards. Though a significant amount of work has been done on detecting obstacles, not much attention has been given to the detection of drop offs, e.g., sidewalk curbs, downward stairs, and other hazards where an error could lead to disastrous consequences. In this paper, we propose algorithms for detecting obstacles in an urban setting using stereo vision and Two-Stage Dynamic Programming (TSDP) technique. We are developing computer vision algorithms for sensing important terrain features as an aid to blind navigation, which interpret visual information obtained from images collected by cameras mounted on camera legs nearly as high as young person. This paper focuses specifically on a novel computer vision algorithm for detecting obstacles, which are important and ubiquitous features on and near sidewalks and other walkways. A fast and robust stereo matching algorithm is proposed that uses only features in order to find a semi-dense disparity map. It works by growing from a small set of correspondence seeds. In this paper we use Normalized Cross-correlation (NCC) function matching with a 5 x 5 window and prepare an edge detected matching table t and start growing disparity components by drawing a seed s from S which is computed using Sobel edge detector, and adding it to t. It results in high accuracy and performance. The obstacle identified in the proposed method which appears in the disparity map enters the phase of depth computing.
References
[1] A. Murarka and e. al, ""Detecting Obstacles and Drop-offs using Stereo and Motion Cues for Safe Local Motion,"" in IEEE/RSJ International conference on Intelligent Robots and Systems, 2008, pp. 702-708.

[2] S. Rahman, ""Obstacle Detection for Mobile Robots Using Computer Vision,"" Department of Computer Science University of York Final Year Project, 2005.

[3] O. Ringdahl, ""Techniques and Algorithms for Autonomous Vehicles in Forest Environment,"" Department of Computing Science Umeå University Licentiate Thesis 978-91-7264-373-4, 2007.

[4] W. Samakming and J. Srinonchat, ""Development Image Processing Technique for Climbing Stair of Small Humanoid Robot,"" in International Conference on Computer Science and Information Technology, 2008, pp. 616-619.

[5] C. Y. Sung, T. S. Jin, and J. M. Lee, ""Optimal Moving Windows for Real-Time Road Image Processing,"" Journal of Robotic Systems 20(2), 65–77 (2003), vol. 20, no. 2, pp. 65-77, 2003.

[6] A. Angelova, L. Matthies, D. Helmick, and P. Perona, ""Learning and Prediction of Slip from Visual Information,"" Journal of Field Robotics, vol. 24, no. 3, p. 205–231, 2007.

[7] P. Foggia, ,. J.-M. Jolion, A. Limongiello, and M. Vento, ""Stereo Vision for Obstacle Detection: a Graph-Based Approach,"" in 6th IAPR – TC-15 Workshop on Graph-based Representations in Pattern Recognition, 2007, pp. 11-13.

[8] S. Thrun and e. al, ""Stanley: The Robot that Won the DARPA Grand Challenge,"" Journal of Field Robotics, 2006.

[9] S. Meers and K. Ward, ""A vision system for providing 3D perception of the environment via transcutaneous electro-neural stimulation,"" in The 8th International Conference on Information, 2004, pp. 546-552.

[10] G. balakrishnan, G. Sainarayanan, R. Nagarajan, and S. Yaccob, ""On stereo processing procedure applied towards blind navigation aid-SVETA,"" in The 8th International Symposium on Signal Processing and Its Applications, 2005, pp. 567-570.

[11] J. Gutmann, M. Fukuchi, and M. Fujita, ""Real-time path planning for humanoid robot navigation,"" in IJCAI, 2005.

[12] j. Coughlan and H. Shen, ""TERRAIN ANALYSIS FOR BLIND WHEELCHAIR USERS: COMPUTER VISION ALGORITHMS FOR FIND-ING CURBS AND OTHER NEGATIVE OBSTACLES,"" in Conference & Workshop on Assistive Technologies for People with Vision & Hearing Impairments Assistive Technology for All Ages CVHI, 2007.

[13] D. Sharstein, r. Szeliski, and R. Zabih, ""A taxonomy and evaluation of dense two-frame stereo correspondence algorithms,"" in IJCV, 2002, p. 7–42.

[14] p. Bellutta, r. Manduchi, l. Matthies, K. Owens, and A. Rankin, ""Ter-rain Perception for DEMO III,"" in Intelligent Vehicle Symposium, 2000.

[15] P. Moallem and K. Faez, ""Effective Parameters in Search Space Re-duction Used in a Fast Edge-Based Stereo Matching,"" Journal of Circuits, Systems, and Computers, vol. 14(2), pp. 249-266, 2005.

[16] A. Stein and M. Hebert, ""Local detection of occlusion boundaries in video,"" in BMVC, 2006.

[17] S. B. Pollard, J. E. W. Mayhew, and J. P. Frisby, ""PMF: A stereo cor-respondence algorithm using a disparity gradient constraint. Perception,"" Perception, vol. 14, pp. 449-470, 1985.

[18] R. M. Perception and L. G. Shapiro, ""Image segmentation techniques,"" CVGIP, vol. 29, pp. 100-132, 1985.

[19] G. balakrishnan, G. Sainarayanan, R. Nagarajan, and S. Yaccob, ""On stereo processing procedure applied towards blind navigation aid-SVETA,"" in The 8th International Symposium on Signal Processing and Its Applications, 2005, pp. 567-570.

[20] S. Lankton, ""Sparse Field Methods - Technical Report,"" Georgia Institute of Technology, 2009.

[21] J. Cech and R. Sara, ""Efficient Sampling of Disparity Space for Fast and Accurate Matching,"" in BenCOS Workshop CVPR, 2007.

[22] R. Sara, ""Finding the largest unambiguous component of stereo matching.,"" in ECCV, 2002, pp. 900-914.

[23] S. Radim, ""Robust Correspondence Recognition for Computer Vi-sion.,"" in 17th Conference of IASC-ERS , Roma, 2006.

[24] D. Gusfield and R. W. Irving, ""The Stable Marriage Problem: Structure and Algorithms,"" in The MIT Press,, 1989.

[25] H. Mohammadi D., S. Shirazi Tehrani, and P. Moallem, ""A Novel Obstacle Detection Method using Stereo Vision and two-stage Dynamic Programming,"" in IEEE/ICEE, 2010.

[26] D. Scharstein and R. Szeliski, ""Stereo matching with nonlinear diffusion,” International Journal of Computer Vision,"" vol. 28, p. 155–174, 1998.

[27] D. Jones and J. Malik, ""Computational framework for determining stereo correspondence from a set of linear spatial filters,"" image processing, vol. 76, p. 321–331, 2000.

[28] Y. S. Kim, J. Lee, and Y. Ha, ""Stereo matching algorithm based on modified wavelet decomposition process,"" Pattern Recognition,, vol. 30, p. 929–952, 1997.

[29] j. Chul Kim and e. al, ""A Dense Stereo Matching Using Two-Pass Dynamic Programming with Generalized Ground Control Points,"" in IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005, p. 1075–1082.

[30] M. Gong and Y. H. Yang, ""Fast Stereo Matching Using Reliability-Based Dynamic Programming and Consistency Constraints,"" in Ninth IEEE International Conference on Computer Vision , 2003.

[31] S. Birchfield and C. Tomasi, ""Depth discontinuities by pixel-to-pixel stereo”,,"" International Journal of Computer Vision,, p. 269–293, 1999.

[32] B. Tang, D. Ait-Boudaoud, B. J. Matuszewski, and L. k. Shark, ""An Efficient Feature Based Matching Algorithm for Stereo Images,"" in Proceed-ings of the Geometric Modeling and Imaging-New Trends (GMAI‟06), 2006, pp. 195-202.

[33] C. Sun, ""Fast Algorithms for Stereo Matching and Motion Estimation,"" in in Proceedings of Australia-Japan Advanced Workshop on Computer Vision,, Adelaide, 2003, pp. 38-48.

[34] A. Donate, Y. Wang, X. Liu, and E. Collins, ""Efficient and Accurate Subpixel Path Based Stereo Matching,"" in 19th International Conference on Pattern Recognition, IEEE, 2008.

[35] ,. S. Fazli, H. Mohammadi D, and P. Moallem, ""Obstacle Detection using Sum of Haming Distance,"" in ICEEE, 2009, pp. 23-30.

[36] S. Fazli, H. Mohammadi D, and P. Moallem, ""A Robust Obstacle Detection Method in Highly Textured Environments using Stereo Vision,"" in 2nd international conference on machine vision (IEEE),, 2009, pp. 97-100.

Untitled Page