Abstract
In this paper, we present an approach for tracking an object in video captured on a mobile device. We use a colour-based approach. The performance of many of these approaches degrades due to lighting changes and occlusion. To address the issue of lightning changes, our approach makes use of colour histogram that is generated by accumulating histograms derived from target objects imaged under different conditions. A CAMShift tracking algorithm is applied to the back-projected image to track the target object.
We have tested our approach by tracking an Emergency Exit sign and the results obtained show that the tracking is robust against lightning changes.
Chapter PDF
Similar content being viewed by others
References
Yilmaz, A., Javed, O., Shah, M.: Object Tracking: A Survey. ACM Computing Survey 38, 1–45 (2006)
Bradski, G.R.: Computer Vision Face Tracking for Use in a Perceptual User Interface. Intel Technology Journal (1998)
Yuan, L., Mu, Z.-C.: Ear Detection Based on Skin-Color and Contour Information. In: 6th International Conference on Machine Learning and Cybernetics, vol. 4, pp. 2213–2217. IEEE, Hong Kong (2007)
Yilmaz, A., Li, X., Shah, M.: Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras. In: IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 26, pp. 1531–1536. IEEE Computer Society (2004)
Yang, D., Xia, J.: Face Tracking Based on Camshift Algorithm and Motion Prediction. In: International Workshop on Intelligent Systems and Applications, pp. 1–4. IEEE, Wuhan (2009)
Exner, D., Bruns, E., Kurz, D., Grundhofer, A., Bimber, O.: Fast and Robust CAMShift Tracking. In: Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 9–16. IEEE, San Francisco (2010)
Yue, Y., Gao, Y., Zhang, X.: An Improved Camshift Algorithm Based on Dynamic Background. In: 1st International Conference on Information Science and Engineering, pp. 1141–1144. IEEE, Nanjing (2009)
Allen, J.G., Xu, R.Y.D., Jin, J.S.: Object Tracking Using Camshift Algorithm and Multiple Quantized Feature Spaces. In: 5th Pan-Sydney Area Workshop on Visual Information Processing, pp. 3–7. ACM, Australia (2004)
Sural, S., Qian, G., Pramanik, S.: Segmentation and Histogram Generation Using the HSV Color Space for Image Retrieval. In: International Conference on Image Processing, vol. 2, pp. 589–592. IEEE (2002)
Swain, M.J., Ballard, D.H.: Indexing via Colour Histogram. In: Active Perception and Robotic Vision, vol. 83, pp. 261–273. Springer (1992)
Yoo, T.-W., Oh, I.-S.: A Fast Algorithm for Tracking Human Faces Based on Chromatic Histograms. In: Patter Recognition Letters, vol. 20, pp. 967–968. Elsevier (1999)
Chen, T.M., Luo, R.C., Hsiaso, T.H., Chia-Yi: Visual Tracking Using Adaptive Colour Histogram Model. In: 25th Annual Conference of IEEE, vol. 3, pp. 1336–1341. IEEE, San Jose (1999)
Fan, L., Riihimaki, M.: A Feature-Based Object Tracking Approach for Real Time Image Processing on Mobile Devices. In: 17th International Conference on Image Processing. IEEE, Hong Kong (2010)
Gong, J., Jiang, Y., Xiong, G., Guan, C., Tao, G., Chen, H.: The Recognition and Tracking of Traffic Lights Based on Colour Segmentation and CAMShift for Intelligent Vehicles. In: Intelligent Vehicles Symposium (IV), pp. 431–435. IEEE, San Diego (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 IFIP International Federation for Information Processing
About this paper
Cite this paper
Mohammed, A.D., Morris, T. (2014). A Robust Visual Object Tracking Approach on a Mobile Device. In: Linawati, Mahendra, M.S., Neuhold, E.J., Tjoa, A.M., You, I. (eds) Information and Communication Technology. ICT-EurAsia 2014. Lecture Notes in Computer Science, vol 8407. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55032-4_19
Download citation
DOI: https://doi.org/10.1007/978-3-642-55032-4_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-55031-7
Online ISBN: 978-3-642-55032-4
eBook Packages: Computer ScienceComputer Science (R0)