Title of dissertation: KEY-FRAME APPEARANCE ANALYSIS FOR VIDEO SURVEILLANCE Kyongil Yoon, Doctor of Philosophy, 2005 Dissertation directed by: Professor Larry Davis Department of Computer Science Tracking moving objects is a commonly used approach for understanding surveillance video. However, by focusing on only a few key-frames, it is possible to effectively perform tasks such as image segmen...

Traditionally the topic of key frame animation has been too complex a topic to be covered in introductory computer graphics courses. The difficulties in including this topic have stemmed from the need for relatively difficult mathematical concepts such as B-spline interpolation in order to generate frames for the animation. In this paper we present improvements to a pedagogical tool called Grap...

We present a practical, key-frame based scribble propagation framework. Our method builds upon recent advances in spatiotemporal filtering by adding key-components required for achieving seamless temporal propagation. To that end, we propose a temporal propagation scheme for eliminating holes in regions where no motion path reaches reliably. Additionally, to facilitate the practical use of our ...

Content based video indexing and retrieval has its foundations in the analyses of the prime video temporal structures. Consequently, technologies for video segmentation and key-frame extraction have become crucial for the development of advanced digital video systems. Conventional algorithms for video partitioning and keyframe extraction are mainly implemented autonomously. By focusing the anal...

In Video Surveillance System, the surveillance of video in its different application such as performing real time online event detection, crime prevention, scene analysis and offline analysis and retrieval of interested events requires very huge computation and memory too. Key frame Extraction (KFE) is selection of frames which represents the object moves and changes in subsequent frames in the...

We present in this paper an intelligent video data visualization tool, based on semantic classification, for retrieving and exploring a large scale corpus of videos. Our work is based on semantic classification resulting from semantic analysis of video. The obtained classes will be projected in the visualization space. The graph is represented by nodes and edges, the nodes are the keyframes of ...

This paper presents a novel approach for extracting discriminative descriptions of 3-D objects using spatio-temporal information. In particular, local features are tracked in image sequences leading to local trajectories containing dynamic information. These trajectories are judged with respect to their quality and robustness and finally each of them is assigned a single local descriptor from a...

This paper describes a method for video retrieval system based on local invariant region descriptors. A novel framework is proposed for combined video segmentation, content extraction and retrieval. A similarity measure, previously proposed by the authors based on local region features, is used for video segmentation. The local regions are tracked throughout a shot and stable features are extra...

As multimedia applications are rapidly spread at an ever-increasing rate, the call for efficient and effective methodologies for organizing and manipulating these data becomes a necessity. One of the basic problems that encounters such systems is to find efficient ways to summarize the huge amount of data involved. In this work two sets of algorithms are proposed in order to effectively select ...

In this paper a new reference image approach for real world surveillance applications is presented. The presented algorithm is composed of two steps. In the first step, A statistical test is performed between a reference and a current image, and a decision is made whether there is a change at a given pixel position. In the second decision step, the possibility to update a reference frame is pro...