Player identification in soccer videos
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
Sports Video Annotation Using Enhanced HSV Histograms in Multimedia Ontologies
ICIAPW '07 Proceedings of the 14th International Conference of Image Analysis and Processing - Workshops
Scene text extraction using modified cylindrical distance
NNECFSIC'12 Proceedings of the 12th WSEAS international conference on Neural networks, fuzzy systems, evolutionary computing & automation
Scene text recognition and tracking to identify athletes in sport videos
Multimedia Tools and Applications
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Player identification is important task in sport video content analysis. In case of soccer video player numbers can be exploited to perform recognition. Jersey numbers can be considered as scene text and main problems in localization and recognition are low resolution, low contrast, color aliasing, unconstrained background etc. This paper proposed new method for player number localization and recognition. Firstly jersey regions are extracted using region growing algorithm. These regions are segmented using the component of HSV color space that best separates jersey and number area. Then, novel method for player number localization based on internal contours is proposed. False number candidates are discarded based on area and aspect ratio. Extracted numbers are enhanced using image smoothing and rotation normalization. We also propose algorithm that improves OCR recognition performance using temporal redundancy.