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The porTiVity project is developing a converged rich media iTV system, which integrates broadcast and mobile broadband delivery to portables and mobiles and which will enable the end-user to act on moving objects within TV programmes. The developments of the project include the playout of portable rich media iTV and the middleware, data and presentation engine in the handheld receiver. In this demonstration,...
This paper presents a novel and effective approach for multi-video summarization: Video Maximal Marginal Relevance (Video-MMR), which extends a classical algorithm of text summarization, Maximal Marginal Relevance. Video-MMR rewards relevant keyframes and penalizes redundant keyframes, as MMR does with text fragments. Two variants of Video-MMR are suggested, and we propose a criterion to select the...
In this paper, we propose a novel method inspired by the bio-informatics domain to parse a rushes video into scenes and takes. The Smith-Waterman algorithm provides an efficient way to compare sequences by comparing segments of all possible lengths and optimizing the similarity measure. We propose to adapt this method in order to detect repetitive sequences in rushes video. Based on the alignments...
Most previous works on video summarization target on a single video document. With the popularity of video corpus (e.g. news video archives) and Web videos, video article that consists of a set of relevant videos are frequently confronted by users. By the traditional single-document summarization, these videos are treated independently and the results are usually redundant due to the lack of inter-video...
During the last years, the development of rushes video summarization systems has greatly increased thanks to the international evaluation campaign TRECVID. In this paper, we propose an automation of the manual TRECVID evaluation using machine learning techniques. We train an automatic assessor to perform evaluation on summary content and we show a high correlation between the manual evaluation performed...
Video summarization is a useful tool which allows a user to grasp rapidly the essence of a video. In the development of this research topic we propose a new method based on different individual content segmentation and selection tools in a collaborative system. The main innovation of this work is to merge results from different approaches, so as to benefit from their respective qualities. Our system...
Evaluation remains an important difficulty in the development of video summarization systems. Rigorous evaluation of video summaries generated by automatic systems is a complicated process because the ground truth is often difficult to define, and even when it exists, it is difficult to match with the obtain results. The TRECVID BBC evaluation campaign has recently introduced a rushes summarization...
This paper reports some work undertaken during the development of a generic object tracking application based on a keypoint model. In our previous work, we proposed a keypoint labeling algorithm to distinguish object from background keypoints. This article is the continuation of this work and deals with the problem of handling object deformation using the keypoint labels. In consequence, we introduce...
This paper studies the problem of background/object differentiation in a keypoint-based tracking application where the object is delimited with a bounding box. We present a keypoint labeling algorithm based on four features: the label of the matched keypoint, color, motion, and position. We discuss methods to best exploit these features, then we detail our labeling algorithm and validate it with some...
In this paper, we propose a novel approach to summarize rushes. Our processing is composed of several steps. First, we remove unusable content and we dynamically accelerate video according to motion activity to maximize the content per time unit. Then, one-second video segments are clustered into similarity clusters. The most important nonredundant pieces of shot are selected such that they maximize...
This paper presents an original approach to video shot retrieval, which is an adaptation of the common text-based paradigm. The idea of our approach is to describe images using a small number of visual elements chosen in a visual dictionary. The user may select some elements from the visual dictionary to compose a query and search for specific video shots. In our approach, we automatically compute...
In this paper, we study the problem of the fast selection of video objects, as an aid for the efficient semi-automatic annotation of video programs. In a regular system, the user has to draw a bounding box around the object, requiring at least two clicks on the image. We propose and experiment algorithms that allow the selection by indicating only one point inside the object, therefore requiring only...
In this paper, we propose a new type of multi-dimensional hidden Markov model based on the idea of dependency tree between positions. This simplification leads to an efficient implementation of the re-estimation algorithms, while keeping a mix of horizontal and vertical dependencies between positions. We explain DT-HMM and we present the formulas for the maximum likelihood re-estimation. We illustrate...
The GMF4iTV project (Generic Media Framework for Interactive Television) is an IST European project that developed an end-to-end broadcasting platform providing interactivity on heterogeneous multimedia devices such as set-top-boxes, PCs and PDAs according to the multimedia home platform (MHP) part of the DVB standard. The developed platform allows the content providers to create enhanced audiovisual...
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