Detecting multiple objects under partial occlusion by integrating classification and tracking approaches

A visual‐based framework for detecting in real time multiple objects in real outdoor scenes is presented. The main novelty of the system is its capability to reduce the problems of partial occlusions and/or overlaps that occur very commonly in real scenes containing multiple moving objects. Overlaps and occlusions are dealt with by integrating classification and tracking procedures into a data‐fusion distributed sensory network. Neural tree‐based networks are applied to distinguish among isolated objects and groups of objects on the image plane. Extended Kalman filters are applied to estimate the number of objects in the scene, their position, and the related motion parameters. Experimental results on complex outdoor scenes with multiple moving objects are presented. © 2001 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 11, 263–276, 2000

[1]  Stuart E. Dreyfus,et al.  Applied Dynamic Programming , 1965 .

[2]  Ming-Kuei Hu,et al.  Visual pattern recognition by moment invariants , 1962, IRE Trans. Inf. Theory.

[3]  Lennart Ljung,et al.  The Extended Kalman Filter as a Parameter Estimator for Linear Systems , 1979 .

[4]  Richard T Lacoss.  Distributed Sensor Networks , 1978 .

[5]  Robert M. Haralick,et al.  The Consistent Labeling Problem: Part I , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Ramesh C. Jain,et al.  Illumination independent change detection for real world image sequences , 1989, Comput. Vis. Graph. Image Process..

[7]  Ernst D. Dickmanns,et al.  An integrated spatio-temporal approach to automatic visual guidance of autonomous vehicles , 1990, IEEE Trans. Syst. Man Cybern..

[8]  C. Tomasi.  Detection and Tracking of Point Features , 1991 .

[9]  Hon Fung Li,et al.  Shapes Recognition Using the Straight Line Hough Transform: Theory and Generalization , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Stuart Russell,et al.  Symbolic Traffic Scene Analysis Using Dynamic Belief Networks , 1993 .

[11]  Jitendra Malik,et al.  Robust Multiple Car Tracking with Occlusion Reasoning , 1994, ECCV.

[12]  Steven S. Beauchemin,et al.  The computation of optical flow , 1995, CSUR.

[13]  Henry Leung.  Neural network data association with application to multiple‐target tracking , 1996 .

[14]  Carlo S. Regazzoni,et al.  Distributed data fusion for real-time crowding estimation , 1996, Signal Process..

[15]  Jake K. Aggarwal,et al.  Tracking human motion using multiple cameras , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[16]  Gian Luca Foresti,et al.  Object detection and tracking in time-varying and badly illuminated outdoor environments , 1998 .

[17]  Gian Luca Foresti.  A Line Segment Based Approach for 3D Motion Estimation and Tracking of Multiple Objects , 1998, Int. J. Pattern Recognit. Artif. Intell..

[18]  François Brémond,et al.  Tracking multiple nonrigid objects in video sequences , 1998, IEEE Trans. Circuits Syst. Video Technol..

[19]  Carlo S. Regazzoni,et al.  Advanced Video-Based Surveillance Systems , 1998 .

[20]  Gian Luca Foresti,et al.  Outdoor Scene Classification by a Neural Tree-Based Approach , 1999, Pattern Analysis & Applications.

[21]  Gian Luca Foresti,et al.  Object recognition and tracking for remote video surveillance , 1999, IEEE Trans. Circuits Syst. Video Technol..

[22]  Michael G. Strintzis,et al.  Spatiotemporal segmentation and tracking of objects for visualization of videoconference image sequences , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[23]  Larry S. Davis,et al.  Hydra: multiple people detection and tracking using silhouettes , 1999, Proceedings 10th International Conference on Image Analysis and Processing.

[24]  Carlo S. Regazzoni,et al.  Statistical morphological skeleton for representing and coding noisy shapes , 1999 .

[25]  Johnson I. Agbinya,et al.  Multi-Object Tracking in Video , 1999, Real Time Imaging.

[26]  Gian Luca Foresti,et al.  Real‐time detection of multiple moving objects in complex image sequences , 1999 .