Search Tracker: Human-derived object tracking in-the-wild through large-scale search and retrieval

Humans use context and scene knowledge to easily localize moving objects in conditions of complex illumination changes, scene clutter and occlusions. In this paper, we present a method to leverage human knowledge in the form of annotated video libraries in a novel search and retrieval based setting to track objects in unseen video sequences. For every video sequence, a document that represents motion information is generated. Documents of the unseen video are queried against the library at multiple scales to find videos with similar motion characteristics. This provides us with coarse localization of objects in the unseen video. We further adapt these retrieved object locations to the new video using an efficient warping scheme. The proposed method is validated on in-the-wild video surveillance datasets where we outperform state-of-the-art appearance-based trackers. We also introduce a new challenging dataset with complex object appearance changes.Comment: Under review with the IEEE Transactions on Circuits and Systems for Video Technolog

Optical memory disks in optical information processing

We describe the use of optical memory disks as elements in optical information processing architectures. The optical disk is an optical memory devicew ith a storage capacity approaching 1010b its which is naturally suited to parallel access. We discuss optical disk characteristics which are important in optical computing systems such as contrast, diffraction efficiency, and phase uniformity. We describe techniques for holographic storage on optical disks and present reconstructions of several types of computer-generated holograms. Various optical information processing architectures are described for applications such as database retrieval, neural network implementation, and image correlation. Selected systems are experimentally demonstrated

Language-based multimedia information retrieval

This paper describes various methods and approaches for language-based multimedia information retrieval, which have been developed in the projects POP-EYE and OLIVE and which will be developed further in the MUMIS project. All of these project aim at supporting automated indexing of video material by use of human language technologies. Thus, in contrast to image or sound-based retrieval methods, where both the query language and the indexing methods build on non-linguistic data, these methods attempt to exploit advanced text retrieval technologies for the retrieval of non-textual material. While POP-EYE was building on subtitles or captions as the prime language key for disclosing video fragments, OLIVE is making use of speech recognition to automatically derive transcriptions of the sound tracks, generating time-coded linguistic elements which then serve as the basis for text-based retrieval functionality

Mean-shift analysis for image and video applications

Cataloged from PDF version of article.In this thesis, image and video analysis algorithms are developed. Tracking moving objects in video have important applications ranging from CCTV (Closed Circuit Television Systems) to infrared cameras. In current CCTV systems, 80% of the time, it is impossible to recognize suspects from the recorded scenes. Therefore, it is very important to get a close shot of a person so that his or her face is recognizable. To take high-resolution pictures of moving objects, a pan-tiltzoom camera should automatically follow moving objects and record them. In this thesis, a mean-shift based moving object tracking algorithm is developed. In ordinary mean-shift tracking algorithm a color histogram or a probability density function (pdf) estimated from image pixels is used to represent the moving object. In our case, a joint-probability density function is used to represent the object. The joint-pdf is estimated from the object pixels and their wavelet transform coefficients. In this way, relations between neighboring pixels, edge and texture information of the moving object are also represented because wavelet coefficients are obtained after high-pass filtering. Due to this reason the new tracking algorithm is more robust than ordinary mean-shift tracking using only color information. A new content based image retrieval (CBIR) system is also developed in this thesis. The CBIR system is based on mean-shift analysis using a joint-pdf. In this system, the user selects a window in an image or an entire image and queries similar images stored in a database. The selected region is represented using a joint-pdf estimated from image pixels and their wavelet transform coefficients. The retrieval algorithm is more reliable compared to other CBIR systems using only color information or only edge or texture information because the jointpdf based approach represents both texture, edge and color information. The proposed method is also computationally efficient compared to sliding-window based retrieval systems because the joint-pdfs are compared in non-overlapping windows. Whenever there is a reasonable amount of match between the queried window and the original image window then a mean-shift analysis is started.Cüce, Halil İbrahimM.S

Exploiting multimedia in creating and analysing multimedia Web archives

The data contained on the web and the social web are inherently multimedia and consist of a mixture of textual, visual and audio modalities. Community memories embodied on the web and social web contain a rich mixture of data from these modalities. In many ways, the web is the greatest resource ever created by human-kind. However, due to the dynamic and distributed nature of the web, its content changes, appears and disappears on a daily basis. Web archiving provides a way of capturing snapshots of (parts of) the web for preservation and future analysis. This paper provides an overview of techniques we have developed within the context of the EU funded ARCOMEM (ARchiving COmmunity MEMories) project to allow multimedia web content to be leveraged during the archival process and for post-archival analysis. Through a set of use cases, we explore several practical applications of multimedia analytics within the realm of web archiving, web archive analysis and multimedia data on the web in general

Monitoring the manul: guidelines for practitioners

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