@conference {13097,
	title = {Concurrent transition and shot detection in football videos using Fuzzy Logic},
	booktitle = {Image Processing (ICIP), 2009 16th IEEE International Conference on},
	year = {2009},
	month = {2009/11//},
	pages = {4341 - 4344},
	abstract = {Shot detection is a fundamental step in video processing and analysis that should be achieved with high degree of accuracy. In this paper, we introduce a unified algorithm for shot detection in sports video using fuzzy logic as a powerful inference mechanism. Fuzzy logic overcomes the problems of hard cut thresholds and the need to large training data used in previous work. The proposed algorithm integrates many features like color histogram, edgeness, intensity variance, etc. Membership functions to represent different features and transitions between shots have been developed to detect different shot boundary and transition types. We address the detection of cut, fade, dissolve, and wipe shot transitions. The results show that our algorithm achieves high degree of accuracy.},
	keywords = {analysis;inference, boundary;shot, Color, colour, detection;sports, functions;shot, histogram;concurrent, logic;image, logic;inference, mechanism;intensity, mechanisms;sport;video, processing;, processing;videonanalysis;fuzzy, signal, transition;edgeness;football, variance;membership, video;video, videos;fuzzy},
	doi = {10.1109/ICIP.2009.5413648},
	author = {Refaey,M.A. and Elsayed,K.M. and Hanafy,S.M. and Davis, Larry S.}
}
@article {18206,
	title = {Dynamic resource allocation via video content and short-term traffic statistics},
	journal = {Multimedia, IEEE Transactions on},
	volume = {3},
	year = {2001},
	month = {2001/06//},
	pages = {186 - 199},
	abstract = {The reliable and efficient transmission of high-quality variable bit rate (VBR) video through the Internet generally requires network resources be allocated in a dynamic fashion. This includes the determination of when to renegotiate for network resources, as well as how much to request at a given time. The accuracy of any resource request method depends critically on its prediction of future traffic patterns. Such a prediction can be performed using the content and traffic information of short video segments. This paper presents a systematic approach to select the best features for prediction, indicating that while content is important in predicting the bandwidth of a video hit stream, the use of both content and available short-term bandwidth statistics can yield significant improvements. A new framework for traffic prediction is proposed in this paper; experimental results show a smaller mean-square resource prediction error and higher overall link utilization},
	keywords = {allocation;link, allocation;multimedia, allocation;variable, bit, codes;, content;bandwidth, error;short, Internet;dynamic, patterns;variable, prediction, rate, resource, segments;short-term, statistics;traffic, systems;resource, traffic, utilization;mean-square, video, video;video},
	isbn = {1520-9210},
	doi = {10.1109/6046.923818},
	author = {M. Wu and Joyce,R.A. and Wong,Hau-San and Guan,Long and Kung,Sun-Yuan}
}
