Author: Amr Ahmed
New paper accepted in ICPR 2014 – “Compact Signature-based Compressed Video Matching Using Dominant Colour Profiles (DCP)”
The paper “Compact Signature-based Compressed Video Matching Using Dominant Colour Profiles (DCP)” has been accepted in the ICPR 2014 conference http://www.icpr2014.org/, and will be presented in August 2014, Stockholm, Sweden.
Abstract— This paper presents a 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 Colour Profile (DCP); a sequence of dominant colours 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 is utilizing the DC-image as a base for extracting colour 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.
Congratulations and well done for Saddam.
Analysis and experimentation results of using DC-image, and comparisons with full image (I-Frame), can be found in Video matching using DC-image and local features (http://eprints.lincoln.ac.uk/12680/)
“DC-Image for Real Time Compressed Video Matching” published in Springer Transactions on Engineering Technologies
New chapter titled “DC-Image for Real Time Compressed Video Matching” is published in Springer Transactions on Engineering Technologies 2014 .
Well done and congratulations to Saddam Bekhet.
Video Matching
Video Matching Using DC-image and Local Features Saddam Bekhet, Amr Ahmed, Andrew Hunter
Paper (PDF): Video Matching Using DC-image and Local Features – WCE2013_pp2209-2214
Video Demos: … soon..
INTRODUCTION:
Videos, especially the compressed ones, became a major part of our daily life. With the amount of videos growing exponentially, Scientists are being pushed to develop robust tools that could efficiently index and retrieve videos in a way similar to human perception of similarity.
*Based on http://www.youtube.com/yt/press/statistics.html
PROBLEM
§Manual annotation is a hard work and annotations are not always available for utilization.
§We need more smarter tagging process for videos.
§With the increasing of compressed videos, more efficient techniques are required to work directly on compressed files, without need for decompression.
AIM
Our aim is to build a framework that will operate on compressed videos (utilizing the DC-images sequence),
CONCLUSION
•DC-IMAGE is suitable for cheaper computations and could be used as basic building block for real-time processing.
•Local features proved to be effective on DC-image, after our introduced modification.
Dr Amjad Altadmri – Graduation Ceremony
Congratulations to Dr Amjad Altadmri for completeing his PhD degree. Amjad received his PhD degree in the formal September Graduation Ceremony at the Lincoln Cathedral.
- Amjad Graduation Ceremony – September 2013
His PhD titled “Semantic Annotation of Domain-Independent Uncontrolled Videos, Incorporating Visual Similarity and Commonsesne Knowledge Bases”. The work produced a Framework for semantic video annotation. In addition, VisualNet was also produced, which is a semantic Network for Visual-related applications.
The photo shows Dr Amjad Altadmri (Left) with his Director of Studies/Supervisor Dr Amr Ahmed ( right).
A list of publications of Amjad’s PhD are below:
- A framework for automatic semantic video annotation
Altadmri, Amjad and Ahmed, Amr (2013) A framework for automatic semantic video annotation. Multimedia Tools and Applications, 64 (2). ISSN 1380-7501. - Semantic levels of domain-independent commonsense knowledgebase for visual indexing and retrieval applications
Altadmri, Amjad and Ahmed, Amr and Mohtasseb Billah, Haytham (2012) Semantic levels of domain-independent commonsense knowledgebase for visual indexing and retrieval applications. Neural Information Processing. Lecture Notes in Computer Science, 7663 . pp. 640-647. ISSN 0302-9743 - VisualNet: commonsense knowledgebase for video and image indexing and retrieval application
Alabdullah Altadmri, Amjad and Ahmed, Amr (2009) VisualNet: commonsense knowledgebase for video and image indexing and retrieval application. In: IEEE International Conference on Intelligent Computing and Intelligent Systems, 21-22 November 2009, Shanghai, China.. - Automatic semantic video annotation in wide domain videos based on similarity and commonsense knowledgebases
Altadmri, Amjad and Ahmed, Amr (2009) Automatic semantic video annotation in wide domain videos based on similarity and commonsense knowledgebases. In: The IEEE International Conference on Signal and Image Processing Applications (ICSIPA 2009), 18-19th November 2009, Malaysia. - Video databases annotation enhancing using commonsense knowledgebases for indexing and retrieval
Altadmri, Amjad and Ahmed, Amr (2009) Video databases annotation enhancing using commonsense knowledgebases for indexing and retrieval. In: The 13th IASTED International Conference on Artificial Intelligence and Soft Computing., September 7 � 9, 2009, Palma de Mallorca, Spain..
Amjad has also participated, with Amr and other members of the DCAPI group, in various workshops especially the V&L EPSRC Network workshops. They presented sessions and showed posters; see related blog posts:
- Two Presentations and Posters in the Vision & Language Network workshop (Dec. 2012, Sheffield) : https://amrahmed.blogs.lincoln.ac.uk/2012/12/22/two-presentations-and-posters-in-the-vision-language-network-workshop/
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V&L Network workshop, Brighton (September 2011): https://amrahmed.blogs.lincoln.ac.uk/2011/09/19/vl-network-workshop-brighton/