Vehicle Classification on Multi-Sensor Smart Cameras Using Feature- and Decision-Fusion

In the proposed project we are working towards multi-sensor smart cameras, i.e., we augment vision-based cameras by additional sensors such as infrared and audio and, thus, transform a single smart camera into an embedded multi-sensor node. Our software framework for embedded online data fusion, called I-SENSE, which supports data fusion on different levels of data abstraction is presented. Further our fusion model is presented with the focus set on four main parts, namely (i) the acoustic and visual feature extraction, (ii) feature based data fusion and the feature selection algorithm, (iii) feature based decision modeling based on support vector machines (SVM) and (iv) decision modeling based on a modified Dempster-Shafer approach is discussed. Finally we demonstrate the feasibility of our multilevel data fusion approach with experimental results of our "vehicle classification" case study.

[1]  B. Ripley,et al.  Pattern Recognition , 1968, Nature.

[2]  Ronald W. Schafer,et al.  Digital Processing of Speech Signals , 1978 .

[3]  Dorothea Heiss-Czedik,et al.  An Introduction to Genetic Algorithms. , 1997, Artificial Life.

[4]  Yoram Singer,et al.  Improved Boosting Algorithms Using Confidence-rated Predictions , 1998, COLT' 98.

[5]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[6]  Yoram Singer,et al.  Improved Boosting Algorithms Using Confidence-rated Predictions , 1998, COLT' 98.

[7]  Johan A. K. Suykens,et al.  Least squares support vector machine classifiers: a large scale algorithm , 1999 .

[8]  Brian A. Baertlein,et al.  Feature-Level and Decision-Level Fusion of Noncoincidently Sampled Sensors for Land Mine Detection , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[10]  H. Durrant-Whyte,et al.  Data Fusion in Decentralised Sensing Networks , 2001 .

[11]  Behzad Moshiri,et al.  Pseudo information measure: a new concept for extension of Bayesian fusion in robotic map building , 2002, Inf. Fusion.

[12]  Volodymyr Turchenko,et al.  Smart license plate recognition system based on image processing using neural network , 2003, Second IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2003. Proceedings.

[13]  Jay Chang,et al.  Vehicle counting and classification algorithms for unattended ground sensors , 2003, SPIE Defense + Commercial Sensing.

[14]  Rama Chellappa,et al.  Vehicle detection and tracking using acoustic and video sensors , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[15]  Bernhard Rinner,et al.  I-SENSE: Intelligent Embedded Multi-Sensor Fusion , 2006, 2006 International Workshop on Intelligent Solutions in Embedded Systems.

[16]  Bernhard Rinner,et al.  Distributed embedded smart cameras for surveillance applications , 2006, Computer.

[17]  Bernhard Rinner,et al.  DSP based acoustic vehicle classification for multi-sensor real-time traffic surveillance , 2007, 2007 15th European Signal Processing Conference.

[18]  Bernhard Rinner,et al.  Enhanced Least Squares Support Vector Machines for Decision Modeling in a Multi-Sensor Fusion Framework , 2007, Artificial Intelligence and Pattern Recognition.

[19]  Bernhard Rinner,et al.  An audio-visual sensor fusion approach for feature based vehicle identification , 2007, 2007 IEEE Conference on Advanced Video and Signal Based Surveillance.

[20]  Arthur P. Dempster,et al.  A Generalization of Bayesian Inference , 1968, Classic Works of the Dempster-Shafer Theory of Belief Functions.