Dissolve Detection in a video sequence based on Animate Vision (original) (raw)
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Dissolve detection in abstract video contents
2011
We propose a straightforward intensity-based dissolve detection method which is able to cope with the particular constraints of the artistic animated movie domain. It uses the hypothesis that during a dissolve, the amount of fading-out and fading-in pixels should be high. Instead of just applying a global threshold, as most of the existing approaches do, we use a twin-threshold approach coped with shape analysis of the signal. This approach allows to reduce false detections caused by steep intensity uctuations as well as to retrieve dissolves caught up in other visual effects. Experimental tests show that whether classic approaches tends to fail, the proposed method provides a good detection even for very complex content setups (e.g. global movement, temporal discontinuity).
A motion-tolerant dissolve detection algorithm
IEEE Transactions on Multimedia, 2005
Gradual shot change detection is one of the most important research issues in the field of video indexing/retrieval. Among the numerous types of gradual transitions, the dissolve-type gradual transition is considered the most common one, but it is also the most difficult one to detect. In most of the existing dissolve detection algorithms, the false/miss detection problem caused by motion is very serious. In this paper, we present a novel dissolve-type transition detection algorithm that can correctly distinguish dissolves from disturbance caused by motion. We carefully model a dissolve based on its nature and then use the model to filter out possible confusion caused by the effect of motion. Experimental results show that the proposed algorithm is indeed powerful.
Effective Algorithm for Detection of Dissolve in Presence of Motion and Illumination
International Journal of Computer Applications, 2016
The detection of dissolve transition is more difficult than detecting fade in and fade out. In this transition, the last frames in the previous shot fade out and the beginning frames in the next shot fade in i.e. the overlapping of fade out and fade in occurs. The dissolves may be of three or more number of frames. In some videos very short dissolve of even three frames also occurs. So, there are lots of challenges in detection of dissolves. Also illumination and camera / object motion gives rise to false positives thereby degrading the algorithm performance. Many researchers addressed this issue but could not achieve the robustness in the presence of illumination and object / camera motion. Therefore this issue needs to be resolved. An algorithm has been proposed for dissolve detection. In this algorithm, color histogram difference between consecutive frames is calculated and average value of this difference for all consecutive frames is used as a metric for dissolve detection.
Intensity-driven dissolve detection adapted to synthetic video contents
Journal of Electronic Imaging, 2013
In this paper we approach the problematic of video temporal segmentation. We propose an intensitybased dissolve detection approach that is able to perform on animated video contents. It uses the hypothesis that during a dissolve, the amount of fading-out and fading-in pixels should be significant compared to other visual transitions. We use this information as a visual discontinuity function. Instead of just applying a global threshold to filter these values, as most of the existing approaches do, we use a twin-thresholding approach and the shape analysis of the discontinuity measure. This allows us to reduce false detections caused by steep intensity fluctuations, as well as to retrieve dissolves caught up in other visual transitions (e.g. caused by movement, color effects, etc.). Experimental tests conducted on more than 452 dissolve transitions show that whether classic approaches tend to fail, the proposed method is able to provide good performance achieving average precision and recall ratios above 94% and 79.6%, respectively.
Analysis-by-synthesis dissolve detection
Proceedings. International Conference on Image Processing, 2002
This paper presents a novel, real-time, minimal-latency technique for dissolve detection which handles the widely varying camera techniques, expertise, and overall video quality seen in amateur, semi-professional, and professional video footage. We achieve 88% recall and 93% precision for dissolve detection. In contrast, on the same data set, at a similar recall rate (87%), DCD has more than 3 times the number of false positives, giving a precision of only 81% for dissolve detection.
10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010), 2010