Noha Ghatwary and Alyaa Amer attended the Medical Imaging Summer School that was held in Favignana, Sicily. They had the chance to engage with around 160 medical image researchers and share their knowledge through discussion and reading groups.
The school held several lectures that discussed different topics presented by different Lectures expert in that field. Also, Noha Ghatwary had the chance to present the accepted paper “Liver CT Enhancement using Fractional Differentiation and Integration” in the poster session and discuss it with the attendees.
Saddam Bekhet presented his accepted paper in ICPR2014 , Stockholm, Sweden
The paper title is “Compact Signature-based Compressed Video Matching Using Dominant Colour Profiles (DCP) ”
Abstract— This paper presents a novel technique for efficient and generic matching of compressed video shots, through compact signatures extracted directly without decompression. The compact signature is based on the Dominant Color Profile (DCP); a sequence of dominant colors extracted and arranged as a sequence of spikes in analogy to the human retinal representation of a scene. The proposed signature represents a given video shot with ~490 integer values, facilitating for real-time processing to retrieve a maximum set of matching videos. The technique is able to work directly on MPEG compressed videos, without full decompression, as it utilizes the DC-image as a base for extracting color features. The DC-image has a highly reduced size, while retaining most of visual aspects, and provides high performance compared to the full I-frame. The experiments and results on various standard datasets show the promising performance, both the accuracy and the efficient computation complexity, of the proposed technique.
Members of DCAPI have presented and showed their research work in the Annual Showcase Event for the School of Computer Science, University of Lincoln. (14th and 15th May). Saddam also won the “Best Demo” prize for his video matching & retrieval interactive demo.
Postgraduates by Research (PGRs) had all day on Wed 14th May and featured in the morning of Thursday 15th May as well, with visitors and companies representatives.
The event is organised by Dr Amr Ahmed (Leader of the DCAPI group, and the Program Leader for PGRs), for a number of years.
The event was also officially opened (and concluded) by the Head of School, Dr David Cobham, who attended the full program and handed the certificates to winners as well as the Helpers, including the Admin team.
All had fun during the Poster session and inbetween the sessions as well.
Interested in joining us as a “Research Fellow”?
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Welcome to the DCAPI research group.
Our multi-disciplinary research is mainly focused on the analysis and mining of digital contents (Visual; images and videos, and textual). This includes Computer Vision, Image/Video Processing and analysis, Semantic Analysis, annotation, Action recognition, Image/Video Matching and similarity (Copy & Near-Duplicate detection), and many others.
We welcome any discussion and potential collaboration. Please get in touch with us (contacts on the right side-bar).
This paper presents a suggested framework for video matching based on local features extracted from the DC-image of MPEG compressed videos, without decompression. The relevant arguments and supporting evidences are discussed for developing video similarity techniques that works directly on compressed videos, without decompression, and especially utilising small size images. Two experiments are carried to support the above. The first is comparing between the DC-image and I-frame, in terms of matching performance and the corresponding computation complexity. The second experiment compares between using local features and global features in video matching, especially in the compressed domain and with the small size images. The results confirmed that the use of DC-image, despite its highly reduced size, is promising as it produces at least similar (if not better) matching precision, compared to the full I-frame. Also, using SIFT, as a local feature, outperforms precision of most of the standard global features. On the other hand, its computation complexity is relatively higher, but it is still within the real-time margin. There are also various optimisations that can be done to improve this computation complexity.
Saddam Bekhet, member of the DCAPI group presented a short presentation about his PhD work “Video similarity in compressed domain” at the school of computer science postgraduate monthly seminar on 13/03/2013 .