Ball and Field Line Detection for Placed Kick Refinement

Classifying video content into different semantic granularities is a possible way for flexible video indexing, browsing and retrieval. In this paper, a placed kick refinement algorithm is proposed after semantic based event detection or manually annotation. The placed kick event is further classified into following three types: free kick, corner kick and penalty according to the ball and field lines detection and their relationships determination. Firstly, we carry out ball detection in the global shot of the placed kick event. According to the ball detection results, we further determine whether to detect field lines using Hough transform. Finally, the ball and field lines detection results are integrated in decision making stage. Experimental results show the effectiveness of the proposed method.

I. Introduction

With the ever increasing amount of multimedia information available in the internet and digital video libraries, efficient video analysis, summarization, indexing and retrieval are urgently needed. Current video content management systems support retrieval using low-level audio-visual features. However, the semantic gap becomes a challenge problem in the management and utilization of the video content management system. Semantic gap is caused by the low level media content descriptors and the superior human beings, since the media content descriptions extracted from videos are too shallow compared to the meaning that users expect to capture [1]. In order to meet the various needs of different users during video retrieval, it is popular to segment video sequences into semantic types [1], [4] and mining vast relationships and concepts in various granulites from video data [1], [2].