Paper Info
Title
Key-frame extraction and key-frame rate determination using human attention modeling
Abstract
This paper presents a novel key-frame detection method that combines the visual saliency-based attention features with the contextual game status information for sports videos. First, it describes the approach of extracting the object oriented visual attention map and illustrates the algorithm for determining the contextual excitement curve. Semantic contextual inference is used to simulate how the video content attracts the subscribers. Second, it presents the fusion methodology of visual and contextual attention analysis based on the characteristics of human excitement. Finally, the experimental results demonstrate the efficiency and the robustness of our system by means of some baseball game videos.
Year
DOI
Venue
2011
10.1109/ICME.2011.6012109
ICME
Keywords
Field
DocType
human excitement,contextual game status information,contextual excitement curve,key-frame rate determination,contextual attention analysis,visual saliency-based attention feature,fusion methodology,human attention modeling,semantic contextual inference,baseball game video,key-frame extraction,visual attention map,indexes,object oriented,sport,content analysis,zinc
Computer vision,Content analysis,Video retrieval,Inference,Computer science,Robustness (computer science),Visual attention,Artificial intelligence,Baseball game,Key frame,Visual saliency
Conference
ISSN
Citations 
PageRank 
1945-7871
1
0.41
References 
Authors
6
1
Name
Order
Citations
PageRank
Huang-Chia Shih118721.98