Temporal Feature Induction for Baseball Highlight Classification

Michael Fleischman, Brandon Roy, Deb Roy


Most approaches to highlight classification in the sports domain exploit only limited temporal information. This paper presents a method, called temporal feature induction, which automatically mines complex temporal information from raw video for use in highlight classification. The method exploits techniques from temporal data mining to discover a codebook of temporal patterns that encode long distance dependencies and duration information. Preliminary experiments show that using such induced temporal features significantly improves performance of a baseball highlight classification system.

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