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Automatic Movie Content Analysis

The MoCA Project

The MoCA Project

MoCA Project:
Analysis and Retargeting of Ball Sports Video

The quality achieved by simply scaling a sports video to the limited display resolution of a mobile device is often insufficient. As a consequence, small details like the ball or lines on the playing field become unrecognizable. We present a novel approach to analyzing court-based ball sports videos. We have developed new techniques to distinguish actual playing frames, to detect players, and to track the ball. This information is used for advanced video retargeting, which emphasizes essential content in the adapted videos.

System overview

Our sports video analysis and adaptation system is based on four modules which analyze a video and one additional module for video retargeting (see the following figure). In a first step, the system distinguishes playing frames from other frames. Additional modules detect court lines, players, objects, and the ball. For each frame, the components are run one after another. Only if a frame is processed successfully in the current step, it is forwarded to the next module. So, for example, if the court field is not detected in a frame, algorithms to locate court lines or players are skipped. Previously computed data is re-used wherever possible.

The adaptation of a frame depends on the results of the analysis. A frame is scaled if no semantic information could be derived. Otherwise, the advanced video retargeting module uses all available information to adapt a frame.

System overview

The following figure shows exemplary intermediate results of the processing steps. From left to right: court model, background image, difference image, player and object segmentation.

System overview: steps

Additional material

Sports video adaptation results

preview of sample video

(automatic zoom
on player)
advanced video retargeting

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