Abstract
This paper presents an efficient way of indexing and searching based on object-specific feature for video retrieval at different semantic levels. By tracking individual objects with segmented data, we generate motion trajectories with moving trails of objects and set a model using polynomial curve fitting. The trajectory model is used as an indexing key for accessing each object in the semantic level. The proposed searching system supports various types of queries including query-by-example, query- by-sketch and query on weighting parameters for event-based retrieval. When retrieving the interested video clips, the system returns the best-matched events in the similarity order. In addition, we implement a temporal event graph for direct accessing and browsing a specific event in the video sequence.
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