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Recent researches have paid more and more attention to traffic sign recognition due to its important role in the intelligence transportation system. In the traditional methods for this task, first the traffic signs are located using the color or shape information of the traffic signs, then a classifier is applied for classification. In this paper, we propose a novel framework using the sparse model...
The most prevailing approach now for parking lot vehicle detection system is to use sensor-based techniques such as ultrasound and infrared-light sensors. A few engineering firms provide camera-based systems, which are only for underground and indoor parking lots due to the poor accuracy of the detector. The main impediments to the camera-based system in applying to outdoor parking lots are adherent...
Existing bus travel time prediction methods only provide a point prediction value of bus travel time. Relevance vector machine (RVM) is proposed for solving the problem. By using a probabilistic Bayesian learning framework, RVM can provide probabilistic prediction and obtain prediction value and variance of prediction error. For making use of historical data and current information, the running time...
Multi-view tracking of objects in video surveillance consists in segmenting and automatically following them through different camera views. This may be achieved using geometric methods, e.g. by calibrating camera sensors and using their transformation matrices. However, in practice the precision of calibration is a major issue when trying to achieve this task robustly. In this paper, we present an...
Trained detectors are the most popular algorithms for the detection of vehicles or pedestrians in video sequences. To speed up the processing time the trained stages build a cascade of classifiers. Thereby the classifiers become more powerful from stage to stage. The most popular classifier for real-time applications is Adaboost applied to rectangular Haar-like features. The processing time of these...
High accuracy and fast recognition speed are two requirements for real-time and automatic license plate recognition system. In this paper, we propose a hierarchically combined classifier based on an inductive learning based method and an SVM-based classification. This approach employs the inductive learning based method to roughly divide all classes into smaller groups. Then the SVM method is used...
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