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Adaptive methods of moving car detection in monocular image sequences

Kasprzak W.

Machine Graphics and Vision

2000

Vol. 9, No. 1/2

167-185

Computer vision applications for traffic scene analysis and autonomous navigation (driver support) require highly sophisticated sensors and computation method- they constitute a real challenge for image analysis systems. Common to bith applications is the moving object detection/tracking task. In this paper we study this task on four different data abstraction levels: image segmentation, 2-D object tracking, model-based 3-D object tracking and many-object traffic scene description. Two meanings of the term "adaptive" are considered: learning algorithm or connectionist systems and recursive estimation for dynamic systems. Generally the firts approach may be appled for low- and segmentation-level analysis of finite image seguences, whereas the second approach for 2-D and 3-D object tracking and estimation.