| Summary: | 碩士 === 國立臺灣大學 === 資訊工程學研究所 === 95 === Tracking in human inhabited environment is a daunting task. High crowdedness causes challenging data association problems. Different motion patterns from a wide variety of moving objects make motion modeling difficult. Accompanying
with traditional motion modeling techniques, this paper introduces a scene interaction model and a neighboring object interaction model to respectively take long-term and short-term interactions between the tracked objects and its surroundings into account. With the use of the interaction models, anomalous activity recognition is accomplished easily. In addition, move-stop hypothesis tracking is applied to deal with move-stop-move maneuvers. The proposed approaches have been demonstrated using data from a laser scanner mounted on the PAL1 robot. Interacting pedestrians, bicycles, motorcycles, cars and trucks are successfully tracked in difficult situations with occlusion.
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