We propose a method for tracking of objects contained in video sequences. Each video object is represented by a set of polygonal regions. A bottom up approach (spatial segmentation/motion estimation) is applied for the initialisation of the method, a limited human interaction is used to build the semantic map of the first frame in video sequence. The tracking of this model along a video sequenc...

In this article, we proposed a surveillance video retrieval method based on detection of moving objects and researched on key problems in surveillance video, such as moving objects detection, video segmentation, selection and description of key frames, and measurement of feature similarities. We detected moving objects via movement detection algorithm based on codebook, and realized automatic s...

In this paper, we propose a novel technique for video shot segmentation and classiication based on the Singular Value Decomposition (SVD). For the input video sequence, we create a feature-frame matrix A, and perform the SVD on it. From this SVD, we are able to not only derive the reened feature space to better segment the video sequence along time axis, but also deene metrics to enable classii...

In this paper we propose an innovative combination strategy for a system using video and audio stream of a news video to automatically segment it into stories. In our approach, the segmentation is performed in two steps: first, shots are classified by combining three different anchor shot detection algorithms using video information only. Then, the shot classification is improved by using a nov...

In this paper, we propose a framework to extendsemantic labeling of images to video shot sequences and achieveefficient and semantic-aware spatiotemporal video segmentation.This task faces two major challenges, namely the temporal vari-ations within a video sequence which affect image segmentationand labeling, and the computational cost of region labeling.Guided by these...

More and more universities and corporations are starting to provide videotaped lectures online for knowledge sharing and learning. Segmenting lecture videos into short clips by topic can extract the hidden information structure of the videos and facilitate information searching and learning. Manual segmentation has high accuracy rates but is very labor intensive. In order to develop a high perf...

We present a new approach for automatic video scene segmentation and content based indexing. Our approach detects video shots and builds a collection of key frames and representative frames. Scene segmentation and video indexing are based on a temporally windowed principal component analysis of a subsampled version of the video sequence. Two discriminants are derived from the principal componen...

New schemes for video transmission over wireless channels are described. Content based approaches for video segmentation and associated resource allocation are proposed. We argue that for transport over wireless channels, diierent video content requires diierent form of resource allocation. Joint source/channel coding techniques (particularly content/data dependent FEC/ARQ schemes) are used to ...

The paper deals with a novel segmentation technique applicable to colour video sequences. The algorithm uses Fast Marching Method for automatic extraction of semantic objects from natural colour video sequences by joint motion and colour analysis. The algorithm handles background in the same way as other objects, thus it does not need global motion compensation. The number of control parameters...