By Alan Hanjalic
Content-Based research Of electronic Video specializes in basic concerns underlying the advance of content material entry mechanisms for electronic video. It treats issues which are serious to effectively automating the video content material extraction and retrieval techniques, and contains assurance of:- Video parsing,- Video content material indexing and representation,- Affective video content material analysis.In this good illustrated e-book the writer integrates comparable info presently scattered in the course of the literature and combines it with new principles right into a unified theoretical method of video content material research. the fabric additionally indicates rules for destiny research.Systems builders, researchers and scholars operating within the sector of content-based research and retrieval of video and multimedia in most cases will locate this e-book necessary.
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Extra info for Content-based Analysis Of Digital Video
If the ranges and R are consistent, the parameters of the detector can first be optimized on a set of training videos to maximize the detection reliability, and then the shot boundaries can be detected with the same high reliability in an arbitrary video without any human supervision. The highest motion independence show the feature extraction approaches that are based on motion compensation. 11). This ratio is computed after registering the frames, that is, after eliminating the changes in the edge structure due to camera motion.
Maximum-likelihood from incomplete data via the EM algorithm, Journal of Roya; Statistical Society, Vol. 39, pp. : Quantitative comparison of shot boundary detection metrics, Proceedings of IS&T/SPIE Storage and Retrieval for Image and Video Databases, Vol. 3656, pp. 2, pp.
One simple example of the techniques that can be applied for this purpose was already explained in Figure 2-6. Realizing this in practice is, however, rather difficult as the two large negative spikes of the parabolic pattern are generally not sufficiently pronounced due to noise and motion in video. This problem was addressed by Truong et al. [Tru00a, Tru00b], who proposed an improved version of the variance-based detector of Alattar [Ala93]. Truong et al. proposed to exploit the facts that the first derivative of the pattern should be monotonically increasing from a negative to a positive value, the intensity variances of both shots involved should be larger than a given threshold, the dissolve duration usually falls between two well-defined thresholds.