Conference Proceedings


Alan F. Smeaton
Colum Foley
Songyang Lao
Cathal Gurrin
Jinlin Guo


Computer Science

effectiveness sports video scale image processing localization and recognition of scoreboard experimental information storage and retrieval systems sift points matching

Localization and recognition of the scoreboard in sports video based on SIFT point matching (2011)

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.
Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> Subject = Computer Science: Image processing
Ireland -> Dublin City University -> Subject = Computer Science
Ireland -> Dublin City University -> Subject = Computer Science: Information storage and retrieval systems
Ireland -> Dublin City University -> Status = Published

Full list of authors on original publication

Alan F. Smeaton, Colum Foley, Songyang Lao, Cathal Gurrin, Jinlin Guo

Experts in our system

Alan F. Smeaton
Dublin City University
Total Publications: 492
Colum Foley
Dublin City University
Total Publications: 25
Cathal Gurrin
Dublin City University
Total Publications: 238