Real-time Obstacle Detection in Outdoor Environment for Visually Impaired using RGB-D and Disparity Map
Article No.: 8, Pages 1 - 4
Abstract
RGB-D sensor is efficient for real-time obstacle detection, but it still does not work with direct sunlight. In this paper, we present a novel approach for real-time obstacle detection in an outdoor urban environment using stereo images and IR depth information based on dual Microsoft Kinect Xbox 360. Our system performed fast disparity mapping from each pair of images by the sum of absolute differences (SAD), which is a block-matching algorithm, then generated a robust 3D point cloud with the disparity map and IR depth information. Extraction the obstacle from the background was done using random-sample consensus (RANSAC) method. The experiments based on MATLAB R2016a involved comprehensive comparison with several alternative validation parameters including disparity block size, disparity range and morphological close element. The results show the algorithm runtime and error occluded pixel rate.
References
[1]
WHO Media Center. Visual impairment and blindness. Geneva, Switzerland: WHO Fact Sheet, 2016.
[2]
Oh, S.M., Tariq, S., Walker, B., Dellaert, F., Map-Based Priors for Localization. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Sendai, Japan, 28 Sep--2 Oct, 2004.
[3]
Ritz, M., and Koenig, L., Laser technique improves safety for the blind. In International Newsletter on Micro--Nano Integration, vol. 5, Oct, 2005, pp. 39--40.
[4]
Rodríguez, A., Yebes, J.J., Alcantarilla, P.F., Bergasa, L.M., Almazán, J., Cela, A., Assisting the Visually Impaired: Obstacle Detection and Warning System by Acoustic Feedback. Sensors, vol. 12, 2012, pp. 17476--17496.
[5]
Tung-Sing, L., and Gerard, M., Visual Navigation aid for the blind in dynamic environments. In IEEE Conference on Computer Vision and Pattern Recognition Workshops. 23-28 June, 2014. pp. 565--572.
[6]
Vorapatratorn, S., Nambunmee, K., iSonar: An Obstacle Warning Device for the Totally Blind, Journal of Assistive, Rehabilitative & Therapeutic Technologies 2014, 2: 23114, eISSN 2001-6824, vol. 2, Jun, 2014, pp. 1--6.
[7]
Vorapatratorn, S., Teachavorasinskun, K., Chanwarapha, N., Suchato A., Punyabukkana P., Directional Obstacle Warning Device Using Multiple Ultrasonic Transducers for People with Visual Disabilities, In Proceedings of the international Convention on Rehabilitation Engineering & Assistive Technology(i-CREATe2015), Singapore, 5 Nov, 2015, pp. 2--5.
[8]
GDP Research, Australia. (2015, Feb 14). {Online}. Available: http://www.gdp-research.com.au/
[9]
Bay Advanced Technologies Ltd. (2015, Feb 14). {Online}. Available: http://www.batforblind.co.nz/index.htm
[10]
Nurion-Raycal. (2015, Feb 14). {Online}. Available: http://www.lasercane.com/
[11]
Huang, H.C., Hsieh, C.T. and Yeh, C.H., An Indoor Obstacle Detection System Using Depth Information and Region Growth, Sensors, vol. 15(10), Oct, 2015, pp. 27116--27141.
[12]
Pham, H.H., Le, T.L. and Vuillerme, N., Real-Time Obstacle Detection System in Indoor Environment for the Visually Impaired Using Microsoft Kinect Sensor, Journal of Sensors, vol. 501, Oct, 2015, pp. 3754918--3754932.
[13]
Pérez-Yus, A., López-Nicolás, G. and Guerrero, J.J., Detection and modelling of staircases using a wearable depth sensor, In Computer Vision-ECCV 2014 Workshops, Switzerland, 6 Sep, 2014, pp. 449--463.
[14]
Tian, Y., RGB-D Sensor-Based Computer Vision Assistive Technology for Visually Impaired Persons, In Computer Vision and Machine Learning with RGB-D Sensors, Springer International Publishing, 2014, pp. 173--194.
[15]
Khoshelham, K. and Elberink, S.O., Accuracy and resolution of kinect depth data for indoor mapping applications, Sensors, vol. 12(2), Feb, 2012, pp. 1437--1454.
[16]
Howard, I.P. and Rogers, B.J., Binocular vision and stereopsis, Oxford University Press, USA. 1995.
[17]
Heikkila, J. and Silvén, O., A four-step camera calibration procedure with implicit image correction. In Computer Vision and Pattern Recognition Proceedings 1997 IEEE Computer Society Conference, 1997, pp. 1106--1112.
[18]
Bradski, G. and Kaehler, A., Learning OpenCV, Computer vision with the OpenCV library, Oreilly & Associates Inc., USA, 2008.
[19]
Heiko, H., Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information, International Conference on Computer Vision and Pattern Recognition, 2005.
[20]
Otsu, N., A threshold selection method from gray-level histograms, Automatica, vol 11(285-296), 1975, pp. 23--27.
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- Real-time Obstacle Detection in Outdoor Environment for Visually Impaired using RGB-D and Disparity Map
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Published In
July 2016
80 pages
Publisher
Singapore Therapeutic, Assistive & Rehabilitative Technologies (START) Centre
Midview City, Singapore
Publication History
Published: 25 July 2016
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