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The nature of statistical learning theory
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Neural Network-Based Face Detection
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A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
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Automatic Detection of Human Nudes
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Autonomous Driving Goes Downtown
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Non-intrusive Person Authentication for Access Control by Visual Tracking and Face Recognition
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A Real-time Computer Vision System for Measuring Traffic Parameters
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Training Support Vector Machines: an Application to Face Detection
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W4: Who? When? Where? What? A Real Time System for Detecting and Tracking People
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Learning and example selection for object and pattern detection
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Unsupervised and supervised learning in radial-basis-function networks
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Contextual Priming for Object Detection
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Kernel-Based 3D Object Representation
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Face Detection Based on Support Vector Machines
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Pattern Recognition Letters
Multi-cue Pedestrian Detection and Tracking from a Moving Vehicle
International Journal of Computer Vision
Pedestrian detection by means of far-infrared stereo vision
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Sharing Visual Features for Multiclass and Multiview Object Detection
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Computer Vision Approaches to Pedestrian Detection: Visible Spectrum Survey
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Sliding-Windows for Rapid Object Class Localization: A Parallel Technique
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A Performance Evaluation of Single and Multi-feature People Detection
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Pattern Recognition Letters
People detection in low-resolution video with non-stationary background
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Experiments with Rough Set Approach to Face Recognition
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
A System for Rapid Interactive Training of Object Detectors
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PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
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Neurocomputing
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Entropic selection of histogram features for efficient classification
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Pedestrian detection on moving vehicle using stereovision and 2d cue
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Novel and efficient pedestrian detection using bidirectional PCA
Pattern Recognition
Multimedia Tools and Applications
Class-Specific weighted dominant orientation templates for object detection
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Combining fast extracted edge descriptors and feature sharing for rapid object detection
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
Efficient human detection in crowded environment based on motion and appearance information
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
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Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
Segmentation of Pedestrians with Confidence Level Computation
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A novel multiplex cascade classifier for pedestrian detection
Pattern Recognition Letters
Computer Vision and Image Understanding
Detecting pedestrians on a Movement Feature Space
Pattern Recognition
Car detection in sequences of images of urban environments using mixture of deformable part models
Pattern Recognition Letters
Pedestrian detection in far infrared images
Integrated Computer-Aided Engineering
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This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes an object class in terms of an overcomplete dictionary of local, oriented, multiscale intensity differences between adjacent regions, efficiently computable as a Haar wavelet transform. This example-based learning approach implicitly derives a model of an object class by training a support vector machine classifier using a large set of positive and negative examples. We present results on face, people, and car detection tasks using the same architecture. In addition, we quantify how the representation affects detection performance by considering several alternate representations including pixels and principal components. We also describe a real-time application of our person detection system as part of a driver assistance system.