Segmentation is the process of identifying uniform regions based on certain conditions. Segmentation has been used for a long time in image analysis and computer vision for a variety of applications. In particular, there has been a growing interest in video sequence segmentation mainly due to the development of MPEG-4, which enables the content-based manipulation of multimedia data [1,2]. For t...

Dynamic textures can be defined as repetitive patterns that exhibit both spatial and temporal coherence. The problem of capturing this intrinsic behavior of a dynamic texture by learning a model from an input video is addressed. Application of a model-based method to dynamic texture synthesis, video compression and videoediting is demonstrated. Results from a method for segmentation of multiple...

Interactive video editing and analysis has a broad impact but it is still a very challenging task. Real-time video segmentation requires carefully defining how to represent the image content, and hierarchical models have shown their ability to provide efficient ways to access color image data. Furthermore, algorithms allowing fast construction of such representations have been introduced recent...

In this work I investigate spatio-temporal information in a video sequence. The advantage of considering a video sequence as a 3D spatio-temporal function with temporal continuity (rather than merely a discrete collection of 2D images) is demonstrated by two computer vision techniques which I have developed. View Synthesis: Each frame of the video sequence is an intersection of the spatio-tempo...

Temporal video segmentation and classification have been advanced greatly by public benchmarks in recent years. However, such research still mainly focuses on human actions, failing to describe videos a holistic view. In addition, previous tends pay much attention visual information yet ignores the multi-modal nature of videos. To fill this gap, we construct an ‘Ads Video Segmentation’ dataset ...

Traffic video analysis can provide a wide range of useful information such as vehicle identification, traffic flow, to traffic planners. In this paper, a framework is proposed to analyze the traffic video sequence using unsupervised vehicle detection and spatio-temporal tracking that includes an image/video segmentation method, a background learning/subtraction method and an object tracking alg...

The psychovisual analysis and drilling in detail for extracting the content is key for understanding objects & activities in video. The goal to retrieve some desired content from video database in economical and semantic way is challenging one. Typical applications that needs modeling and extracting semantic video content are useful for systems like police investigation, video-on-demand systems...

The new MPEG-4 standard will provide superior services for the user, as it introduces the video objects concept. However, there is no generic segmentation technique able to provide the segmentation maps for such a coding system. In this paper, we propose a novel mesh-based video segmentation and objects tracking algorithm with both robust motion estimation and modeling of motion discontinuities...

With the advent and proliferation of low cost and high performance digital video recorder devices, an increasing number of personal home video clips are recorded and stored by the consumers. Compared to image data, video data is lager in size and richer in multimedia content. Efficient access to video content is expected to be more challenging than image mining. Previously, we have developed a ...