Author: Amr Ahmed

PGRs meeting and Research Presentations – Nov. 2015

Amr Ahmed / / Uncategorized

The monthly PGRs Research Presentations was held on Wed. 11th November, 2pm, Room MC3108.

This session we had the following presentations:

Title: “Profiling User Engagement with Promotional Social Media Content“. Title:   “A Bio-inspired Collision Detection Vision System Embedded for Autonomous Micro-robots  ”

By: Jamie Mahoney

By: Cheng Hu
Abstract: Organisations, retailers and brands have a long-established need to gain insight into the characteristics of their customers, users and online followers. Using Twitter as a case study, we describe a method of creating engagement profiles of users based on qualitative analyses of the social media content with which they have publicly engaged. By clustering these engagement profiles, we extend previous work by not only showing how people within a social graph can be clustered in useful ways, but also how these users are likely to engage with specific types of social media content – thus allowing for the creation of targeted social media content strategies. Our findings demonstrate that ‘traditional’ methods of social graph segmentation do not reflect groupings of similar users in terms of engagement behaviour, we also demonstrate that user engagement behaviours do not vary dramatically over time. We provide suggestions for how these findings might be used in the creation of effective strategies for companies, and organisations, wishing to issue promotional material via social media platforms. Abstract:  The vision system takes inspiration from locusts’ response in detecting fast approaching objects. Neurophysiological research suggested that locusts use a wide-field visual neuron called lobula giant movement detector (LGMD) to respond to imminent collisions. In this work, we present the implementation of selected neuron model by a low-cost ARM processor as part of a composite vision module. The developed system is able to perform image acquisition and processing independently. The vision module is placed on top of a micro-robot to initiate obstacle avoidance behaviour. Both simulation and real-world experiments were carried out to test the reliability and robustness of the vision system. The results of the performed experiments with different scenarios demonstrated the amenability of the developed bio-inspired vision system to be used as a low-cost embedded module in autonomous robots with high precision.

 

 
  • Then our usual catch-up agenda:
  

 

 

 

 

 

StatsDay (Statistics Session)

Amr Ahmed / / Uncategorized

On 28th October 2015, LSoCS PGRs had a StatsDay event, thanks to Dr Phil Assheton for being with us.

The event covered main concepts around the statistics and how it helps in experiments and evaluations, including parametric vs non-parametric techniques, the interpretation of the p-value and what conclusion we can take.

The event also included a hands-on practical part, where participants worked some prepared examples and programmed in R.

Thanks to all involved.

PGRs meeting and Research Presentations – Oct. 2015

Amr Ahmed / / Uncategorized

The monthly PGRs Research Presentations was held on Wed. 14th October, 2pm, Room MC3108.

This session we had the following presentations:

Title: “Modelling LGMD2 Visual Neuron System“. Title:   “Compressed video matching: Frame-to-frame revisited”

By: Qinbing Fu

By: Saddam Bekhet
Abstract: Two Lobula Giant Movement Detectors (LGMDs) have been identified in the lobula region of the locust visual system: LGMD1 and LGMD2. LGMD1 had been successfully used in robot navigation to avoid impending collision. LGMD2 also responds to looming stimuli in depth, and shares most the same properties with LGMD1; however, LGMD2 has its specific collision selective responds when dealing with different visual stimulus. Therefore, in this paper, we propose a novel way to model LGMD2, in order to emulate its predicted bio-functions, moreover, to solve some defects of previous LGMD1 computational models. The mechanism of ON and OFF cells, as well as bio-inspired nonlinear functions, are introduced in our model, to achieve LGMD2’s collision selectivity. Our model has been tested by a miniature mobile robot in real time. The results suggested this model has an ideal performance in both software and hardware for collision recognition. Abstract:  This presentation is about an improved frame-to-frame (F-2-F) compressed video matching technique based on local features extracted from reduced size images, in contrast with previous F-2-F techniques that utilized global features extracted from full size frames. The revised technique addresses both accuracy and computational cost issues of the traditional F-2-F approach. Accuracy is improved through using local features, while computational cost issue is addressed through extracting those local features from reduced size images. For compressed videos, the DC-image sequence, without full decompression, is used. Utilizing such small size images (DC-images) as a base for the proposed work is important, as it pushes the traditional F-2-F from off-line to real-time operational mode. The proposed technique involves addressing an important problem: namely the extraction of enough local features from such a small size images to achieve robust matching. The relevant arguments and supporting evidences for the proposed technique are presented. Experimental results and evaluation, on multiple challenging datasets, show considerable computational time improvements for the proposed technique accompanied by a comparable or higher accuracy than state-of-the-art related techniques.

 

 
  • Then our usual catch-up agenda:
  • PGR Month (as per the GS email).
  • Reminder of the StatsDay session (28th Oct, Lab B).
  • Expected Deadline (for Progress Panel) v.early Nov.
  • Announce @ “App Fest”:
    • Required ~5 supervisors (PGR/MComp):

 

 

 

 

 

PGRs meeting and Research Presentations – Sept. 2015

Amr Ahmed / / Uncategorized

The monthly PGRs Research Presentations is resumed (after Summer Break) and was held on Wed. 9th September, 2pm, Room MC3108.

This session we had the following presentations:

Title: “Affordable Mobile Robotic Platforms for Teaching Computer Science at African Universities“. Title:   “Exploring the dynamics of social interaction in massive open online courses”

By: Ernest Gyebi

By: Kwamena Appiah-Kubi
Abstract: Educational robotics can play a key role in addressing some of the challenges faced by higher education in Africa. One of the major obstacles preventing a wider adoption of initiatives involving educational robotics in this part of the world is lack of robots that would be affordable by African institutions. In this paper, we present a survey and analysis of currently available affordable mobile robots and their suitability for teaching computer science at African universities. To this end, we propose a set of assessment criteria and review a number of platforms costing an order of magnitude less than the existing popular educational robots. Our analysis identifies suitable candidates offering contrasting features and benefits. We also discuss potential issues and promising directions which can be considered by both educators in Africa but also designers and manufacturers of future robot platforms. Abstract:  MOOCs (Massive Open Online Courses) make free and easily accessible educational resources from participating universities spanning a wide range of courses. These learning resources are often structured and delivered to mimic a brick-and-mortar classroom. The courses usually attract large number of participants who have to collaborate within the time frame of the course to facilitate their learning as well as socialize. This large number of participants that have to collaborate within such a short time span presents a new context to investigate the dynamics of social interaction within such a group.

 

 
  • Then our usual catch-up agenda: New regulations and PGRs forms.

 

 

 

 

 

July’s Research Presentation

Amr Ahmed / / Uncategorized

The monthly PGRs Research Presentations was held on Wed.  8th July, 2pm, Room MC3108.

This session we had the following presentations:

Title: “Facilitating Individualised Collaboration with Robots (FInCoR)“.

By: Peter Lightbody

Abstract: Enabling a robot to seamlessly collaborate with a human counterpart on a joint task requires not only the ability to identify human preferences, but also the capacity to act upon this information when planning and scheduling tasks. This presentation provides a review of the current state-of-the-art techniques used in human-robot collaboration; techniques which will be utilised to combine the detection of human preferences with real-time task scheduling. This system will thus allow the collaborator to subconsciously influence the planning and scheduling of the system, eventually creating a seamless and less disruptive collaboration experience. This review is followed by a brief overview of the subsequent stages of research, with a probabilistic model introduced to allow the robot to dynamically adapt to changes during the completion of a task.