Research on medical imaging and video analysis
Congratulations to Saddam who successfully passed his PhD VIVA on 23rd May 2016.
Examiners have commended Saddam’s work and contributions. They also emphasized how well written the thesis is.
A well-deserved achievement Saddam, well done.
And all the best for your future career.
Another successful end of year annual Showcase event, organised by Amr Ahmed for the 4th year.
At the University of Lincoln, School of Computer Science. (6th and 7th May): Annual Showcase Event for the School of Computer Science,
Several companies attended the event, including Google UK, Siemens, QinetiQ, mass, Artsgraphica, Heritage Lincolnshire, to name a few.
They were impressed by the level and quality of the presented work, as well as how students presented and engaged with questions.
Also, DCAPI group participated in the event and Saddam won a prize: http://dcapi.blogs.lincoln.ac.uk/2015/05/13/pgrs-showcase-event-2015/
Saddam next to his poster.
The aim of this project is to investigate how computer vision methods such as object and
action recognition may be assisted by computational linguistic models, such as WordNet.
The main challenge of object and action recognition is the scalability of methods from
dealing with a dozen of categories (e.g. PASCAL VOC) to thousands of concepts (e.g.
ImageNet ILSVRC). This project is expected to contribute to the application of automated
visual content annotation and more widely to bridging the semantic gap between
computational approaches of vision and language.
Deadline: 20th March 2015.
A PhD studentship is advertised at
“Object and Action Recognition Assisted by Computational Linguistics”
The research is collaboration between University of Kingston (Digital Imaging Research Centre) and University of Lincoln (DCAPI group)
For details of the applications process: http://www.kingston.ac.uk/research/research-degrees/funding/phd-studentships-2015/faqs/
Deadline: 20th March 2015
A PhD studentship is advertised at
“Object and Action Recognition Assisted by Computational Linguistics”
The research is collaboration between University of Kingston (Digital Imaging Research Centre) and University of Lincoln (DCAPI group)
For details of the applications process: http://sec.kingston.ac.uk/research/research-degrees/current-research-opportunities/funded/
Deadline: 20th June
Summary: “Object and Action Recognition Assisted by Computational Linguistics”.
The aim of this project is to investigate how computer vision methods such as object and
action recognition may be assisted by computational linguistic models, such as WordNet.
The main challenge of object and action recognition is the scalability of methods from
dealing with a dozen of categories (e.g. PASCAL VOC) to thousands of concepts (e.g.
ImageNet ILSVRC). This project is expected to contribute to the application of automated
visual content annotation and more widely to bridging the semantic gap between
computational approaches of vision and language.
Deadline: 20th June.
Amr organised the Annual Showcase Event for the School of Computer Science, University of Lincoln. (14th and 15th May). This year, the event also featured the Postgraduates by Research (PGRs) presenting their research work and demonstrating some interactive demos.
Members of DCAPI group 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. (more details and photos are available on the group’s website at http://dcapi.blogs.lincoln.ac.uk/2014/05/17/pgrs-showcase-event/)
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/)
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.
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
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.
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:
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:
