Fuzzy framework for unsupervised video content characterization and shot classification

Fuzzy framework for unsupervised video content characterization and shot classification

Video Classification and Shot Detection for Video Retrieval Applications

Appropriate organization of video databases is essential for pertinent indexing and retrieval of visual information. This paper proposes a new feature called Block Intensity Comparison Code (BICC) for video classification and an unsupervised shot change detection algorithm to detect the shot changes in a video stream using autoassociative neural network (AANN) which makes retrieval problems muc...

Supervised classification for video shot segmentation

In this paper, we explore supervised classification methods for video shot segmentation. We transform the temporal segmentation problem into a multi-class categorization issue. This approach provides a uniform framework for using different kinds of features extracted from the video and for detecting various types of shot boundaries. The approach utilizes manual labeled training data and a simpl...

A Comparison of Unsupervised Shot Classification Algorithms for News Video Segmentation

Automatic classification of shots extracted by news video plays an important role in the context of news video segmentation. In spite of the efforts of the researchers involved in this field, a definite solution for the shot classification problem does not yet exist. Moreover, the authors of each novel algorithm usually provide results supporting the claim that their method performs well on a s...

An Unsupervised Method for Real Time Video Shot Segmentation

Segmentation of a video into its constituent shots is a fundamental task for indexing and analysis in content based video retrieval systems. In this paper, a novel approach is presented for accurately detecting the shot boundaries in real time video streams, without any a priori knowledge about the content or type of the video. The edges of objects in a video frame are detected using a spatio-t...