Hanjalic A., Lagendijk R.L., Biemond J.: "Automated Segmentation of Movies into Logical Story Units", Submitted for review to IEEE Transaction of Circuits and Systems for Video Technology, Special Issue on Image and Video Processing for Emerging Interactive Multimedia Services  Home/Search Document Details and Download
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Dissolve Transition Detection Algorithm Using SpatioTemporal.. - Jun, Yoon, Lee (2000) (1 citation) (Correct)
....starts and terminates are very different, and (2) The duration of dissolve transition is typically more than 0.3 second. Keywords Video Segmentation, MPEG, Shot change detection, Dissolve, Fades, Macro block type distribution. 1. INTRODUCTION Shot segmentation [4,5,6,7,9,10] and clustering [2,8] technologies have been developed for non linear video browsing and searching during the last decade. Shot segmentation represents a process of extracting temporal information, such as frame numbers, of each shot of a video based on the transition detection, and shot clustering represents a ....
....running time of test material is about 115min 54sec long. Table.1 summarizes the performance of the presented dissolve detection algorithm. The overall performance of the algorithm is very promising for video segmentation and it can be used as a basic input for shot clustering algorithms such as [2,8]. Since most of dissolve transitions satisfies proposed algorithm ( R1] to [R3] the recall ratio is very high and the miss ratio is very low. Some of miss Figure 4. Typical macro block type distribution in B frames when a wipe transition occurs Intra Interpolated Backward Prediction Forward ....
Hanjalic, A., R. Lagendijk, and J. Biemond, "Automated Segmentation of Movies into Logical Story units," IEEE Transactions on Circuits and Systems for Video Technology (1999)
Template-based Detection of Anchorperson Shots in News.. - Alan Hanjalic Reginald (1998) (1 citation) Self-citation (Hanjalic Lagendijk Biemond) (Correct)
....each shot k of a sequence we now define its similarity with the template shot as s(k) 1 (1) A(t,k) whereby A(t,k) is the dissimilarity between the template t and the shot k. In order to perform the detection of anchorperson shots automatically, we use the adaptive threshold M(k) proposed in [8] and defined as follows: Here w is a fixed parameter whose value is not critical in a wide range of values. The parameter Nk denotes the number of shots until k and since the last detected anchorperson shot. It also uses the similarity value s o of the last shot of the last news report as a bias. ....
....shot. It also uses the similarity value s o of the last shot of the last news report as a bias. For each shot k, a value s(k) is available as well as the threshold value M(k) An anchorperson shot is detected when 4. Dissimilarity measure We now define the dissimilarity metric A(k,n) based on [8], with the intention to reliably distinguish all anchorperson shots from the rest, but at the same time to allow for slight differences among different types of anchorperson shots. As already mentioned in Section 3, the metric A(k,n) measures the dissimilarity between shots k and n by using their ....
Hanjalic A., Lagendijk R.L., Biemond J.: "Automated Segmentation of Movies into Logical Story Units", Submitted for review to IEEE Transaction of Circuits and Systems for Video Technology, Special Issue on Image and Video Processing for Emerging Interactive Multimedia Services
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