Improving Generalization with Active Learning
Machine Learning - Special issue on structured connectionist systems
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Confidence-Based Active Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
A cascade of boosted generative and discriminative classifiers for vehicle detection
EURASIP Journal on Advances in Signal Processing
A novel active heads-up display for driver assistance
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
On-road vehicle detection using evolutionary Gabor filter optimization
IEEE Transactions on Intelligent Transportation Systems
Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Intelligent Transportation Systems
Vehicle and Guard Rail Detection Using Radar and Vision Data Fusion
IEEE Transactions on Intelligent Transportation Systems
Looking-In and Looking-Out of a Vehicle: Computer-Vision-Based Enhanced Vehicle Safety
IEEE Transactions on Intelligent Transportation Systems
On Color-, Infrared-, and Multimodal-Stereo Approaches to Pedestrian Detection
IEEE Transactions on Intelligent Transportation Systems
Automatic Vehicle Detection Using Local Features—A Statistical Approach
IEEE Transactions on Intelligent Transportation Systems
Learning, Modeling, and Classification of Vehicle Track Patterns from Live Video
IEEE Transactions on Intelligent Transportation Systems
Monocular precrash vehicle detection: features and classifiers
IEEE Transactions on Image Processing
A neural network filter to detect small targets in high clutter backgrounds
IEEE Transactions on Neural Networks
WalkSafe: a pedestrian safety app for mobile phone users who walk and talk while crossing roads
Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications
Efficient visual tracking using particle filter with incremental likelihood calculation
Information Sciences: an International Journal
Classification of vehicle type and make by combined features and random subspace ensemble
International Journal of Computational Vision and Robotics
Image-based on-road vehicle detection using cost-effective Histograms of Oriented Gradients
Journal of Visual Communication and Image Representation
An integrative approach to accurate vehicle logo detection
Journal of Electrical and Computer Engineering
Hybrid model of clustering and kernel autoassociator for reliable vehicle type classification
Machine Vision and Applications
Active learning for on-road vehicle detection: a comparative study
Machine Vision and Applications
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This paper introduces a general active-learning framework for robust on-road vehicle recognition and tracking. This framework takes a novel active-learning approach to building vehicle-recognition and tracking systems. A passively trained recognition system is built using conventional supervised learning. Using the query and archiving interface for active learning (QUAIL), the passively trained vehicle-recognition system is evaluated on an independent real-world data set, and informative samples are queried and archived to perform selective sampling. A second round of learning is then performed to build an active-learning-based vehicle recognizer. Particle filter tracking is integrated to build a complete multiple-vehicle tracking system. The active-learning-based vehicle-recognition and tracking (ALVeRT) system has been thoroughly evaluated on static images and roadway video data captured in a variety of traffic, illumination, and weather conditions. Experimental results show that this framework yields a robust efficient on-board vehicle recognition and tracking system with high precision, high recall, and good localization.