Summary
This article presents a shape extraction and results of a preliminary validation stage for a pedestrian detection system based on the use of active contours. The complete system is based on the use of both far infrared and visible cameras to detect areas that potentially contain pedestrians; in order to validate and filter such result a refinement of the human shape by means of active contours is performed followed by a neural network based filtering.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bertozzi, M., Broggi, A., Fascioli, A., Sechi, M.: Shape-based Pedestrian Detection. In: Procs. IEEE Intelligent Vehicles Symposium 2000, Detroit, USA, October. 2000, pp. 215–220 (2000), doi:10.1109/IVS.2000.898344.
Bertozzi, M., Broggi, A., Felisa, M., Vezzoni, G., Del Rose, M.: Low-level Pedestrian Detection by means of Visible and Far Infra-red Tetra-vision. In: Procs. IEEE Intelligent Vehicles Symposium 2006, Tokyo, Japan, June 2006, pp. 231–236 (2006), doi:10.1109/IVS.2006.1689633.
Beymer, D., Konolige, K.: Real-time Tracking of Multiple People using Continuous Detection. In: Procs. Intl. Conf. on Computer Vision, Kerkyra (1999)
Broggi, A., Bertozzi, M., Felisa, M., Grisleri, P., Ghidoni, S., Vezzoni, G., Hilario Gómez, C., Del Rose, M.: Pedestrian Detection by means of Far-infrared Stereo Vision. Computer Vision and Image Understanding 106(2), 194–204 (2007)
Curio, C., Edelbrunner, J., Kalinke, T., Tzomakas, C., von Seelen, W.: Walking Pedestrian Recognition. IEEE Trans. on Intelligent Transportation Systems 1(3), 155–163 (2000)
Cutler, R., Davis, L.S.: Robust Real-time Periodic Motion Detection, Analysis and Applications. IEEE Trans. on Pattern Analysis and Machine Intelligence 22(8), 781–796 (2000)
Dao, M.-S., G., F., Natale, B.D., Massa, A.: Edge potential functions and genetic algorithms for shape-based image retrieval. In: Procs. IEEE Intl. Conf. on Image Processing (ICIP 2003), Barcelona, Spain, September 2003, vol. 2, pp. 729–732 (2003)
Dao, M.-S., Natale, F.G.B.D., Massa, A.: Efficient Shape Matching Using Weighted Edge Potential Function. In: Procs. 13th Intl. Conf. on Image Analysis and Processing (ICIAP 2005), Cagliari, Italy (September 2005)
Del Rose, M., Frederick, P.: Pedestrian Detection. In: Procs. Intelligent Vehicle Systems Symposium, Traverse City, USA (2005)
Gavrila, D.M.: Pedestrian Detection from a Moving Vehicle. In: Procs. of European Conference on Computer Vision, vol. 2, pp. 37–49 (2000)
Kania, R., Del Rose, M., Frederick, P.: Autonomous Robotic Following Using Vision Based Techniques. In: Procs. Ground Vehicle Survivability Symposium, Monterey, USA (2005)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active Contour Models. Intl. Journal of Computer Vision 1(4), 321–331 (1988)
Nanda, H., Davis, L.: Probabilistic Template Based Pedestrian Detection in Infrared Videos. In: Procs. IEEE Intelligent Vehicles Symposium 2002, Paris, France (June 2002)
Philomin, V., Duraiswami, R., Davis, L.: Pedestrian Tracking from a Moving Vehicle. In: Procs. IEEE Intelligent Vehicles Symposium 2000, Detroit, USA, October 2000, pp. 350–355 (2000)
Polana, R., Nelson, R.C.: Detection and Recognition of Periodic, Non-rigid Motion. Internation Journal of Computer Vision 23(3), 261–282 (1997)
Shashua, A., Gdalyahu, Y., Hayun, G.: Pedestrian Detection for Driving Assistance Systems: Single-frame Classification and System level Performance. In: Procs. IEEE Intelligent Vehicles Symposium 2004, Parma, Italy (June 2004)
Shimizu, H., Poggie, T.: Direction Estimation of Pedestrian from Multiple Still Images. In: Procs. IEEE Intelligent Vehicles Symposium 2004, Parma, Italy (June 2004)
Stauffer, C., Grimson, W.E.L.: Similarity Templates for Detection and Recognition. Procs. IEEE Intl. Conf. on Computer Vision and Pattern Recognition 1, 221–228 (2001)
Williams, D.J., Shah, M.: A Fast Algorithm for Active Contours and Curvature Estimation. CVGIP: Image Understanding 55(1), 14–26 (1992)
Zhao, L.: Dressed Human Modeling, Detection, and Parts Localization. Ph.D. dissertation, Carnegie Mellon University (2001)
Zhao, L., Thorpe, C.: Stereo and neural network-based pedestrian detection. IEEE Trans. on Intelligent Transportation Systems 1(3), 148–154 (2000)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Bertozzi, M., Broggi, A., Ghidoni, S., Del Rose, M. (2008). Pedestrian Shape Extraction by Means of Active Contours. In: Laugier, C., Siegwart, R. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75404-6_25
Download citation
DOI: https://doi.org/10.1007/978-3-540-75404-6_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75403-9
Online ISBN: 978-3-540-75404-6
eBook Packages: EngineeringEngineering (R0)