| Paper: | MLSP-P3.4 | ||
| Session: | Pattern Recognition | ||
| Time: | Wednesday, May 17, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Machine Learning for Signal Processing: Signal detection, Pattern Recognition and Classification | ||
| Title: | INTEGRATED DETECTION, TRACKING AND RECOGNITION FOR IR VIDEO-BASED VEHICLE CLASSIFICATION | ||
| Authors: | Xue Mei, University of Maryland, College Park, United States; Shaohua Zhou, Siemens Corporate Research, United States; Hao Wu, University of Maryland, College Park, United States | ||
| Abstract: | We present an approach for vehicle classification in IR video sequences by integrating detection, tracking and recognition. The method has two steps. First, the moving target is automatically detected using a detection algorithm. Next, we perform simultaneous tracking and recognition using an appearance-model based particle filter. The tracking result is evaluated at each frame. Low confidence in tracking performance initiates a new cycle of detection, tracking and classification. We demonstrate the robustness of the proposed method using outdoor IR video sequences. | ||
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