Digital Image Processing
X-means: Extending K-means with Efficient Estimation of the Number of Clusters
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Novel Video Caption Detection Approach Using Multi-Frame Integration
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Detection and Recognition of Scoreboard for Baseball Videos
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Video Event Classification Using Bag of Words and String Kernels
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Localizing and segmenting text in images and videos
IEEE Transactions on Circuits and Systems for Video Technology
A spatial-temporal approach for video caption detection and recognition
IEEE Transactions on Neural Networks
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In broadcast sports video, the scoreboard is attached at a fixed location in the video and generally the scoreboard always exists in all video frames in order to help viewers to understand the match's progression quickly. Based on these observations, we present a new localization and recognition method for scoreboard text in sport videos in this paper. The method first matches the Scale Invariant Feature Transform (SIFT) points using a modified matching technique between two frames extracted from a video clip and then localizes the scoreboard by computing a robust estimate of the matched point cloud in a two-stage non-scoreboard filter process based on some domain rules. Next some enhancement operations are performed on the localized scoreboard, and a Multi-frame Voting Decision is used. Both aim to increasing the OCR rate. Experimental results demonstrate the effectiveness and efficiency of our proposed method.