Object-Based Video Retrieval and Event Detection for Baseball Video

Abstract

In recent few years, the convenience and low cost of obtaining and storing digital video make people eager to have an effective tool for utilizing these data. From the viewpoint of human vision, digital video just keeps track of frames. Since it lacks for semantic information, it is necessary to understand the digital content with human brain. To promote the scope and value of further applications, automatic generation of high-level semantics is necessary. For a general sport video, motion behavior and characteristic of moving objects is an essential feature. In this paper, our goal is to develop an automatic extraction of motion-based feature via a fixed camera. More precisely, we firstly develop the motion-based segmentation and tracking of moving objects. Then, we design the indexing techniques of motion information for further efficient utilization. To demonstrate the effect of extracting motion-based features,we will build a tested platform of motion-based retrieval system.Based on this platform, we will develop an event-based model of baseball video so as to provide high-level captions on the timeline axis.