Real Time Head Detection for Embedded Vision Modules

This paper shows the algorithm implementation for a FPGA based design for people counting using a low level head detection method. Different annular patterns are used to process in parallel the image and detect heads of different sizes. Preprocessing and edge extraction are also made using reconfigurable hardware. The developed system exploits hardware processing as the vision algorithm has been modified and tuned for hardware implementation using almost the 100% of area resources of a Spartan3 (1.5 Mgates) and performing in real time with similar results than other more sophisticated algorithms while using very low cost circuits.

[1]  Roberto Cipolla,et al.  A probabilistic framework for perceptual grouping of features for human face detection , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.

[2]  F Bartolini,et al.  Counting people getting in and out of a bus by real-time image-sequence processing , 1994, Image Vis. Comput..

[3]  M. Mazo,et al.  Detection of moving objects in railway using vision , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[4]  Toshi Takamori,et al.  Head and Face Detection at Indoor Environment by Home Robot , 2000 .

[5]  Nipun Kwatra,et al.  A Framework for Activity Recognition and Detection of Unusual Activities , 2004, ICVGIP.

[6]  Leonidas J. Guibas,et al.  Counting people in crowds with a real-time network of simple image sensors , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[7]  Ignacio Parra,et al.  Pedestrian Detection Using SVM and Multi-Feature Combination , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[8]  Nikolaos Grammalidis,et al.  Head detection and tracking by 2-D and 3-D ellipsoid fitting , 2000, Proceedings Computer Graphics International 2000.

[9]  Stanley T. Birchfield,et al.  Elliptical head tracking using intensity gradients and color histograms , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[10]  Alex Pentland,et al.  Motion regularization for model-based head tracking , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[11]  Qian Chen,et al.  A general framework for tracking people , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[12]  Yoichi Sato,et al.  3D Head Tracking using the Particle Filter with Cascaded Classifiers , 2006, BMVC.