Quantized Wavelet Features and Support Vector Machines for On-Road Vehicle Detection

Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARCV 2002

Volumn , Issue , 2002, Pages 1641-1646

  Sun, Zehang ^a   Bebis, George ^a   Miller, Ronald ^b  

^a University of Nevada   (United States)

^b FORD MOTOR COMPANY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MULTIRESOLUTION ANALYSIS; QUANTIZED WAVELET FEATURES; SUPPORT VECTOR MACHINES; SUPPORT VECTAR MACHINE (SVM); VEHICLE DETECTION; WAVELET DECOMPOSITION;

APPROXIMATION THEORY; FACE RECOGNITION; HIERARCHICAL SYSTEMS; IMAGE RETRIEVAL; MATHEMATICAL MODELS; PRINCIPAL COMPONENT ANALYSIS; STATISTICAL METHODS; VEHICLES; WAVELET TRANSFORMS; ALGORITHMS; PARAMETER ESTIMATION; PROBABILITY DISTRIBUTIONS; REAL TIME SYSTEMS; RISK ASSESSMENT; VECTORS; WAVEFORM ANALYSIS;

FEATURE EXTRACTION; VEHICLE LOCATING SYSTEMS;

EID: 2342419492     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. R. Duda, P. Hart, and D. Stork, Pattern Classification. Jon-Wiley, 2001.
2. N. Matthews, P. An, D. Charnley, and C. Harris, "Vehicle detection and recognition in greyscale imagery," Control Engineering Practice, vol. 4, pp. 473-479, 1996.
3. C. Goerick, N. Detlev and M. Werner, "Artificial neural networks in real-time car detection and tracking applications," Pattern Recognition Letters, vol. 17, pp. 335-343, 1996.
4. H. Schneiderman and T. Kanade, "Probabilistic modeling of local appearance and spatial relationships for object recognition," IEEE International Conference on Computer Vision and Pattern Recognition, pp. 45-51, 1998.
5. H. Schneiderman, A statistical approach to 3D object detection applied to faces and cars. CMU-RI-TR-00-06, 2000.
6. M. Weber, M. Welling, and P. Perona, "Unsupervised learning of models for recognition," European Conference on Comptuer vision, pp. 18-32, 2000.
7. C. Papageorgiou and T. Poggio, "A trainable system for object detection," International Journal of Computer Vision, vol. 38, no. 1, pp. 15-33, 2000.
8. C. Jacobs, A. Finkelstein and D. Salesin, "Fast multiresolution image querying," Proceedings of SIGGRAPH, pp. 277-286, 1995.
9. G. Garcia, G. Zikos, and G. Tziritas, "Wavelet packet analysis for face recognition," Image and Vision Computing, vol. 18, pp. 289-297, 2000.
10. V. Vapnik, The Nature of Statistical Learning Theory. Springer Verlag, 1995.
11. C. Burges, "Tutorial on support vector machines for pattern recognition," Data Mining and Knowledge Discovery, vol. 2, no. 2, pp. 955-974, 1998.
12. G. Bebis, S. Uthiram, and M. Georgiopoulos, "Face detection and verification using genetic search," International Journal on Artificial Intelligence Tools, vol. 9, no. 2, pp. 225-246, 2000.
13. H. Rowley, S. Baluja and T. Kanade, "Neural network-based face detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 1, pp. 23-38, 1998.
14. Z. Sun, X. Yuan, G. Bebis, and S. Louis, "Neural-network-based gender classification using genetic eigen-feature extraction," IEEE International Joint Conference on Neural Networks, 2002(accepted, available from http://www.cs.unr.edu/bebis/Publications.html).