Department of Electrical and Electronics Engineering2024-11-0920031057-714910.1109/TIP.2003.8127582-s2.0-0041663515http://dx.doi.org/10.1109/TIP.2003.812758https://hdl.handle.net/20.500.14288/8137We propose a fully automatic and computationally efficient framework for analysis and summarization of soccer videos using cinematic and object-based features. The proposed framework includes some novel low-level soccer video processing algorithms, such as dominant color region detection, robust shot boundary detection, and shot classification, as well as some higher-level algorithms for goal detection, referee detection, and penalty-box detection. The system can output three types of summaries: i) all slow-motion segments in a game, ii) all goals in a game, and iii) slow-motion segments classified according to object-based features. The first two types of summaries are based on cinematic features only for speedy processing, while the summaries of the last type contain higher-level semantics. The proposed framework is efficient, effective, and robust for soccer video processing. It is efficient in the sense that there is no need to compute object-based features when cinematic features are sufficient for the detection of certain events, e.g., goals in soccer. It is effective in the sense that the framework can also employ object-based features when needed to increase accuracy (at the expense of more computation). The efficiency, effectiveness, and the robustness of the proposed framework are demonstrated over a large data set, consisting of more than 13 hours of soccer video, captured at different countries and conditions.Electrical electronics engineeringJournal Articlehttps://www.scopus.com/inward/record.uri?eid=2-s2.0-0041663515anddoi=10.1109%2fTIP.2003.812758andpartnerID=40andmd5=e0df869a9f16e9d9f29b1186a5eb849eQ18320