Abstract
The face-tracking systems in use often suffer from converging to a false face-like region in a smart home environment. For this, we propose a technique to reduce errors due to false positives in the estimation scheme of face movement. In the proposed method, the face movement is estimated by using the information on face-candidate blobs obtained from the current frame as well as from the previous frame. This estimated face movement information is used in the face tracker for tracking faces in video images. Our experimental result shows a conspicuous improvement in the performance of the face tracking process in terms of success rates and with robustness against interruptions from face-like blobs.
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Bien, Z.Z., Park, K.-H., Jung, J.-W., Jung, J.-W., Do, J.-H.: Intention Reading is Essential in Human-Friendly Interfaces for the Elderly and the Handicapped. IEEE Trans. on Industrial Electronics. 52(6), 1500–1505 (2005)
Ruiz-del-Solar, J., Shats, A., Verschae, R.: Real-time tracking of multiple persons. In: 12th Image Analysis and Processing, pp. 109–114 (2003)
Liu, F., Lin, X., Li, S.Z., Shi, Y.: Multi-Modal Face Tracking Using Bayesian Network. In: IEEE Int’l Workshop on Analysis and Modeling of Faces and Gestures, pp. 135–142 (2003)
Wu, Y., Huang, T.S.: Robust Visual Tracking by Integrating Multiple Cues Based on Co-Inference Learning. Int’l Journal of Computer Vision 58(1), 55–71 (2004)
Deguchi, K., Kawanaka, O., Okatani, T.: Object tracking by the mean-shift of regional color distribution combined with the particle-filter algorithm. In: IEEE Int’l Conf. on Pattern Recognition, pp. 506–509 (2004)
Shan, C., Wei, Y., Tan, T., Ojardias, F.: Real Time Hand Tracking by Computing Particle Filtering and Mean Shift. In: IEEE Conf. on Automatic Face and Gesture Recognition, pp. 669–674 (2004)
Yang, C., Duraiswami, R., Davis, L.: Fast Multiple Object Tracking via a Hierarchical Particle Filter. In: IEEE Conf. on Computer Vision, pp. 212–219 (2005)
Comaniciu, D., Ramesh, V., Meer, P.: Kernel-Based Object Tracking. IEEE Trans. on Pattern Analysis and Machine Intelligence 25(5), 564–577 (2003)
Do, J.-H., Bien, Z.: Effective Cue Integration for Fast and Robust Face Detection in Videos. In: IEEE Conf. on Information Reuse and Integration, pp. 354–359 (2007)
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© 2008 Springer-Verlag Berlin Heidelberg
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Do, JH., Bien, Z. (2008). Robust Face Tracking with Suppressed False Positives in Smart Home Environment. In: Helal, S., Mitra, S., Wong, J., Chang, C.K., Mokhtari, M. (eds) Smart Homes and Health Telematics. ICOST 2008. Lecture Notes in Computer Science, vol 5120. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69916-3_5
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DOI: https://doi.org/10.1007/978-3-540-69916-3_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69914-9
Online ISBN: 978-3-540-69916-3
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