Conference/ProceedingsIS&T/SPIE's Electronic Imaging 2005
Start date16.01.2005
End date20.01.2005
AddressSan Jose, CA USA
Author(s)Hyoung-Gook Kim, Steffen Roeber, Amjad Samour, Thomas Sikora
TitleDetection Of Goal Events In Soccer Videos
AbstractIn this paper, we present an automatic extraction of goal events in soccer videos by using audio track features alone
without relying on expensive-to-compute video track features. The extracted goal events can be used for high-level indexing and selective browsing of soccer videos. The detection of soccer video highlights using audio contents comprises three steps: 1) extraction of audio features from a video sequence, 2) event candidate detection of highlight events based on the information provided by the feature extraction Methods and the Hidden Markov Model (HMM), 3) goal event selection to finally determine the video intervals to be included in the summary. For this purpose we compared the performance of the well known Mel-scale Frequency Cepstral Coefficients (MFCC) feature extraction method vs. MPEG-7 Audio Spectrum Projection feature (ASP) extraction method based on three different
decomposition methods namely Principal Component Analysis( PCA), Independent Component Analysis (ICA) and Non-Negative Matrix Factorization (NMF). To evaluate our system we collected five soccer game videos from various sources. In total we have seven hours of soccer games consisting of eight gigabytes of data. One of five soccer games is used as the training data (e.g., announcers’ excited speech, Audience ambient speech noise, audience clapping,environmental sounds). Our goal event detection results are encouraging.Keywords: Goal score Detection, Highlight events Detection, MPEG-7, Mel-scale
Key wordsGoal score Detection, Highlight events Detection, MPEG-7, Mel-scale Frequency Cepstrum Coefficients