Image segmentation provides a powerful semantic description of video imagery essential in image understanding and efficient manipulation of image data. In particular, segmentation based on image motion defines regions undergoing similar motion allowing image coding system to more efficiently represent video sequences. This paper describes a general iterative framework for segmentation of video ...

We present a video caption detection and recognition system based on a fuzzy-clustering neural network (FCNN) classifier. Using a novel caption-transition detection scheme we locate both spatial and temporal positions of video captions with high precision and efficiency. Then employing several new character segmentation and binarization techniques, we improve the Chinese video-caption recogniti...

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...

We study the problem of segmenting moving objects in unconstrained videos. Given a video, the task is to segment all the objects that exhibit independent motion in at least one frame. We formulate this as a learning problem and design our framework with three cues: (i) independent object motion between a pair of frames, which complements object recognition, (ii) object appearance, which helps t...

We present a novel approach to segmenting video using iterated graph cuts based on spatio-temporal volumes. We use the mean shift clustering algorithm to build the spatio-temporal volumes with different bandwidths from the input video. We compute the prior probability obtained by the likelihood from a color histogram and a distance transform using the segmentation results from graph cuts in the...

Human motion analysis from video has attracted much interest from computer vision researchers due to its promising applications for visual surveillance, perceptual user interface, content-based image storage and retrieval, video conferencing, athletic performance analysis and virtual reality. A key aspect to understand and build computational models of human actions is the capability to tempora...

Temporal segmentation of video is a necessary rst step to indexing digital video for browsing and retrieval. A number of diierent video temporal segmen-tation algorithms have been published in the literature. There has been little eeort to evaluate and characterize their performance so as to deliver a single (or set of) algorithms that may be used by other researchers for indexing video databas...