Localization and recognition of the scoreboard in sports video based on SIFT point matching

Abstract

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.