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Details for article 16 of 16 found articles
| Title: |
Wicket Fall Concept Mining From Cricket Video Using A-Priori Algorithm |
| Author: |
Mahesh Goyani Shreyash Dutta Gunvatsinh Gohil Sapan Naik |
| Appeared in: |
The international journal of multimedia & its applications |
| Paging: | Volume 3 (2011) nr. 1 pages 111-120 |
| Year: |
2011 |
| Contents: |
In this paper, we propose an algorithm to detect semantic concepts from cricket video. In our previous work, we have proposed key frame detection based approach for semantic event detection andclassification. The proposed scheme works in two parts. In first part a top-down event detection and classification is performed using hierarchical tree. In second part, higher level concept is identified by applying A-Priori algorithm. In part 1, key frames are identified based on Hue Histogram difference at level 1. At level 2, logo transitions classify the frames as real-time or replay. At level 3, we classify the real time frames as field view, pitch view or non field view based on thresholds like Dominant Soli PixelRation (DSPR) and Dominant Grass Pixel Ration (DGPR). At level 4, we detect close up and crowd frames based upon edge detection. At level 5a, we classify the close up frames into player of team A,player of team B and umpire based upon skin colour and corresponding jersey colour. At level 5b, we classify the crowd frames into spectators, player’s gathering of team A or player’s gathering of team B. In part two, labels are associated with each frame event, which is used as input to A-Priori algorithm for concept mining. Results at the end of paper show the robustness of our approach. |
| Publisher: |
Academy & Industry Research Collaboration Center (AIRCC) (provided by DOAJ) |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 16 of 16 found articles
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