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The following topics are dealt with: multimedia; ontology; image annotation; image classification; video coding; image retrieval; image segmentation; knowledge acquisition; and image mosaic.
Recent research results in the field of Multimedia Content Analysis (MCA) have been marked by an abundance of theoretical and algorithmic solutions covering narrow application domains only. In this paper we analyze this tendency and its origin in more detail and explain why, in our view, this should not be considered "the way to go" in providing easy access to content in multimedia systems...
Most of the efforts concerning the digital representation of humans (Virtual Humans, or VHs) have been focused on synthesizing geometry for static or animated shapes. The next step is to consider VHs as active semantic entities with features, functionalities, interaction skills, etc. The ontology for VHs we are defining will provide the "semantic layer" required to reconstruct, store, retrieve...
In this paper we consider the problem of automatically annotating images with keywords. We first discuss performance measures for the problem in some length. We propose a new information-theory based measure de-symmetrised mutual information (DTMI). We then describe a straightforward solution to the annotation problem. We first train a set of classifiers to detect the presence of each individual keyword...
This paper proposes a new type of a support vector machine which uses a kernel constituted from fuzzy basis functions. The proposed network combines the characteristics both of a support vector machine and a fuzzy system: high generalization performance, even when the dimension of the input space is very high, structured and numerical representation of knowledge and ability to extract linguistic fuzzy...
In order to be satisfactorily adequate in generating relevant multimodal information, we argue that any multimedia and multimodal ontology has to incorporate three basic criteria. These are: (i) a conceptually and semantically clear distinction between the operational concept of Modality and Media (medium), (ii) describe a set of recursive formal rules that can allocate and vehicle the appropriate...
This paper gives an overview of approaches to video representation targeting semantic analysis for content-based indexing and retrieval. It highlights the major achievements of the existing methodologies and sheds new light to the challenges that are still unsolved. The problem of adaptive representation of digital multimedia is critically assessed and some novel ideas are presented. In addition,...
Hidden Markov Models provide a powerful framework for bridging the semantic gap between low-level video features and high-level user needs by taking full advantage of our prior knowledge on the video structure. A serious flaw of HMMs is that they require all the modalities of a video document to be strictly synchronous before their fusion. Taking as a case study tennis broadcasts analysis, we introduce...
In this paper we present an overview of a software platform that has been developed within the aceMedia project, termed the aceToolbox, that provides global and local lowlevel feature extraction from audio-visual content. The toolbox is based on the MPEG-7 experimental Model (XM), with extensions to provide descriptor extraction from arbitrarily shaped image segments, thereby supporting local descriptors...
In late 2004, a new method of publishing multimedia broadcasts on the Internet became popular called 'Podcasting'. Podcasting incorporates existing feed description formats, namely RSS 2.0 (Really Simple Syndication), to deliver various enclosed files which allows users to subscribe to feeds, receiving updates periodically. Originally intended for self-publishing and syndication of audio files, usage...
This paper outlines a new attention based similarity measure and describes an application to the problem of identifying image clusters in a 4 class problem. A diverse set of images was obtained using camera phones in 4 separate locations and classification performance was tested against the true location of the images. The approach promises to have application to the unsupervised extraction of unknown...
This paper proposed a systematical framework to address the essential problem, the semantic gap between extractable lowlevel features and meaningful high-level semantics, in content-based retrieval. Low-level features, which can be directly extracted from video streams, are color histogram, inter-frame differences, edges, etc. Theoretically, it is possible to detect events from these features based...
We present a method for quantifying and localising changes in two facial scans of the same person taken at two different time instants. The method is based on rigid registration and semantic feature extraction, followed by discrepancy computation. The proposed method combines the Landmark Transform (LT) method, which is applied on semantic feature points, and the Iterative Closest Point (ICP) algorithm,...
This paper presents a novel method based on pre-processing prior to intermediate view interpolation to synthesise an intermediate view as would be viewed by a virtual camera located along the baseline joining the two stereo video cameras. The objective is to achieve virtual eye contact for immersive videoconferencing. An energy minimisation method based on graph cut is used to obtain a disparity map...
Advanced annotation techniques of multimedia data significantly improve representing and retrieving multimedia-based contents. In this paper we present an intelligent framework for attaching semantic annotations to image contents based on the extraction of elementary low-level features, user's relevance feedback, and the usage of ontology knowledge. This approach facilitates image annotation by computing...
In this paper we investigate a subspace modelling technique based on dense motion vector fields for its potential to obtain semantic information about a video sequence. Experiments show the technique's abilities to localize motion over several frames and to spot different motion modes within a scene/shot.
The endoscopic capsule is a recent technological breakthrough with high clinical importance. Exam analysis duration is its main setback, requiring an average of two hours from a trained specialist. Automation is required and this paper presents a topographic segmentation tool using low-level features that can reduce annotation times up to 15 minutes per exam. This is accomplished using Bayesian classifiers...
Pseudo-semantic labeling is a novel approach to organize mobile multimedia content such as images and videos. We have developed low-complexity algorithms to derive labels, such as "indoor/outdoor", "face/not face", that can be run on the mobile device. "Indoor/outdoor" classification is done based on the presence of sky in the images. Skin like pixels are detected based...
As well as words in text processing, image regions are polysemic and need some disambiguation. If the set of representations of two different objects are close or intersecting, a region that is in the intersection will be recognized as being possibly both objects. We propose here a way to disambiguate regions using some knowledge on relative spatial positions between these regions. Given a segmented...
This paper presents a software architecture for digital multimedia content management. The architecture presented is portable and allows complex and powerful content analysis techniques to be deployed on a wide range of devices. It enables the deployment of intelligent pro-active multimedia content and facilitates user tasks when dealing with multimedia content.
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