Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data

This book gives a start-to-finish overview of the whole Fish4Knowledge project, in 18 short chapters, each describing one aspect of the project. The Fish4Knowledge project explored the possibilities of big video data, in this case from undersea video. Recording and analyzing 90 thousand hours of video from ten camera locations, the project gives a 3 year view of fish abundance in several tropical coral reefs off the coast of Taiwan. The research system built a remote recording network, over 100 Tb of storage, supercomputer processing, video target detection and

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Object Tracking Based on Stable Feature Mining Using Intraframe Clustering and Interframe Association

Extracting stable features to enhance object representation has proved to be very effective in improving the performance of object tracking. To achieve this, mining techniques, such as K-means clustering and data associating, are often adopted. However, K-means clustering needs the pre-set number of clusters. Real scenarios (heavy occlusion and so on) often make the tracker lose the target object. To handle these problems, we propose an intraframe clustering and interframe association (ICIA)-based stable feature mining algorithm for object tracking. The value (in HSV space) peak contour is employed to automatically estimate the number of clusters and classify value and saturation colors of the object region to get connected subregions. Every subregion is described with observation and increment models. Multi-feature distances-based subregion association, between the current object template and the current observation, is then utilized to mine stable subregion pairs and obtain feature change ratio. Stable subregion displacements, and current detected and historical trajectories are systematically fused to locate the object. And, stable and unstable subregion features are updated separately to restrain the accumulative error. Experimental comparisons are conducted on six test sequences. Compared with several relevant state-of-the-art algorithms, the proposed ICIA tracker most accurately locates objects in four sequences and shows the second-best performance in the other two sequences with only less 1 pixel distance difference than the best method.Published versio

A scalable approach to video summarization and adaptation

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, octubre de 201

Digital imaging technology assessment: Digital document storage project

An ongoing technical assessment and requirements definition project is examining the potential role of digital imaging technology at NASA's STI facility. The focus is on the basic components of imaging technology in today's marketplace as well as the components anticipated in the near future. Presented is a requirement specification for a prototype project, an initial examination of current image processing at the STI facility, and an initial summary of image processing projects at other sites. Operational imaging systems incorporate scanners, optical storage, high resolution monitors, processing nodes, magnetic storage, jukeboxes, specialized boards, optical character recognition gear, pixel addressable printers, communications, and complex software processes