Automatic soccer video analysis and summarization
University of Rochester · Koç University · +2 more institutions
Abstract
We 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 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; 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,…
Citation impact
- FWCI
- 53.57
- Percentile
- 100%
- References
- 40
Authors
3Topics & keywords
- Automatic summarization
- Computer science
- Robustness (evolution)
- Artificial intelligence
- Object detection
- Computer vision
- Motion detection
- Motion analysis