Abstract
Integral projections can be used, by themselves, to accurately track human faces in video sequences. Using projections, the tracking problem is effectively separated into the vertical, horizontal and rotational dimensions. Each of these parts is solved, basically, through the alignment of a projection signal -a one-dimensional pattern- with a projection model. The effect of this separation is an important improvement in feature location accuracy and computational efficiency. A comparison has been done with respect to the CamShift algorithm. Our experiments have also shown a high robustness of the method to 3D pose, facial expression, lighting conditions, partial occlusion, and facial features.
This work has been supported by the Spanish MCYT grant DPI-2001-0469-C03-01.
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References
Bradski, G.R.: Computer Vision Face Tracking For Use in a Perceptual User Interface. Intel Technology Journal Q2’98 (1998)
Spors, S., Rabenstein, R.: A Real-Time Face Tracker for Color Video. IEEE Intl. Conference on Acoustics, Speech, and Signal Processing, Utah, USA (2001)
Kaucic, R., Blake, A.: Accurate, Real-Time, Unadorned Lip Tracking. Proc. of 6th Intl. Conference on Computer Vision (1998) 370–375
Sobottka, K., Pitas, I.: Segmentation and Tracking of Faces in Color Images. Proc. of 2nd Intl. Conf. on Aut. Face and Gesture Recognition (1996) 236–241
Stiefelhagen, R., Yang, J., Waibel, A.: A Model-Based Gaze Tracking System. Proc. of IEEE Intl. Symposia on Intelligence and Systems (1996) 304–310
Pahor, V., Carrato, S.: A Fuzzy Approach to Mouth Corner Detection. Proc. of ICIP-99, Kobe, Japan (1999) I–667–I–671
Schwerdt, K., Crowley, J. L.: Robust Face Tracking Using Color. Proc. of 4th Intl. Conf. on Aut. Face and Gesture Recognition, Grenoble, France (2000) 90–95
García-Mateos, G., Ruiz, A., López-de-Teruel, P.E.: Face Detection Using Integral Projection Models. Proc. of IAPR Intl. Workshops S+SSPR’2002, Windsor, Canada (2002) 644–653
Isard, M., Blake, A.: Contour Tracking by Stochastic Propagation of Conditional Density. Proc. 4th Eur. Conf. on Computer Vision, Cambridge, UK (1996) 343–356
Vieren, C., Cabestaing, F., Postaire, J.: Catching Moving Objects with Snakes for Motion Tracking. Pattern Recognition Letters, 16 (1995) 679–685
Pentland, A., Moghaddam, B., Starner, T.: View-Based and Modular Eigenspaces for Face Recognition. Proc. CVPR’94, Seattle, Washington, USA (1994) 84–91
La Cascia, M., Sclaro., S., Athitsos, V.: Fast, Reliable Head Tracking Under Varying Illumination: An Approach Based on Registration of Texture-mapped 3D Models. IEEE PAMI, 22(4), (2000) 322–336
Intel Corporation. IPL and OpenCV: Intel Open Source Computer Vision Library. http://www.intel.com/research/mrl/research/opencv/
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Mateos, G.G. (2003). Refining Face Tracking with Integral Projections. In: Kittler, J., Nixon, M.S. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2003. Lecture Notes in Computer Science, vol 2688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44887-X_43
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DOI: https://doi.org/10.1007/3-540-44887-X_43
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