Abstract
Head detection is an important, but difficult task, if no restrictions such as static illumination, frontal face appearance or uniform background can be assumed. We present a system that is able to perform head detection under very general conditions by employing a 3D measurement system namely a structured light distance measurement. An algorithm of head detection from sparse 3D data (19×19 data points) is developed that reconstructs a 3D surface over the image plane and detects head hypotheses of ellipsoidal shape. We demonstrate that detection and rough localization is possible in up to 90% of the images.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Blake A., McCowen D., Lo H. R., Lindsey P. J.: Trinoculuar active range-sensing. IEEE Trans. on Pattern Analysis and Machine Intelligence 15, (1993) 477–483.
Clabian M., Rötzer H., Bischof H.: Tracking structured light pattern. SPIE — Conf. Intelligent Robots and Computer Vision XX: Algorithms, Techniques and Active Vision (2001) 183–192.
Gavrila D. M., Davis L.S.: 3-D model-based tracking of human upper body movement: a multi-view approach. (1995) 253–258.
Grammalidis N., Strintzis M.G.: Head detection and tracking by 2-D and 3-D ellipsoid fitting. IEEE Proc. Int. Conf. Computer Graphics (2000) 221–226.
Heikkilä J., Silven O.: A four-step camera calibration procedure with implicit image correction. Proc. of Int. Conf. on Computer Vision and Pattern Recognition (1997) 1106–1112.
Iwasawa S., Ohya J., Takahashi K., Sakaguchi T., Kawato S., Ebihara K., Morishima S.: Real-time, 3D-estimation of human body postures from trinocular images. Proc. Int. Workshop on Modelling People (1999) 3–10.
Jarvis R.: A perspective on range finding techniques for computer vision, IEEE Trans. on Pattern Analysis and Machine Intelligence 5 (1983) 122–139
Luo R., Guo Y.: Tracking of moving heads in cluttered scenes from stereo vision. Robot Vision (2001) 148–156.
Le Moigne J., Waxman, A.M.: Structured light patterns for robot mobility. IEEE J. of Robotics and Automation 4 (1988) 541–548.
Papageorgiou C., Poggio T.: A trainable system for object detection. Int. J. of Computer Vision 38(1) (2000) 15–33.
Reyna R., Giralt A., Esteve D.: Head detection inside vehicles with a modified SVM for safer airbags. IEEE Proc. Int. Transp. Systems (2001) 268–272.
Stockman G. C., Chen S.-W., Gongzhu H., Shrikhande N.: Sensing and recognition of rigid objects using structured light. IEEE Control System Magazine 8 (1988) 14–22
Trobina M., Leonardis A.: An application of a structured light sensor system to robotics: Grasping arbitrarily shaped 3-D objects from a pile. Proc. IEEE Int. Conf. on Robotics and Automation 1 (1995) 241–246.
Zhang L., Lenders P.: A New Head Detection Method Based on the Region Shield Segmentation in Complex Background. Proc. Int. Symp. on Intell. Multimedia, Video and Speech Processing (2001) 328–331.
Zhang Z.: Flexible camera calibration by viewing a plane from unknown orientations. Proc. of 7th IEEE Int. Conf. on Computer Vision 1 (1999) 666–673.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Clabian, M., Rötzer, H., Bischof, H., Kropatsch, W. (2002). Head Detection and Localization from Sparse 3D Data. In: Van Gool, L. (eds) Pattern Recognition. DAGM 2002. Lecture Notes in Computer Science, vol 2449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45783-6_48
Download citation
DOI: https://doi.org/10.1007/3-540-45783-6_48
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44209-7
Online ISBN: 978-3-540-45783-1
eBook Packages: Springer Book Archive