18 research outputs found
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MC2: MPEG-7 content modelling communities
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe use of multimedia content on the web has grown significantly in recent years. Websites such as Facebook, YouTube and Flickr cater for enormous amounts of multimedia content uploaded by users. This vast amount of multimedia content requires comprehensive content modelling otherwise
retrieving relevant content will be challenging. Modelling multimedia content can be an extremely time consuming task that may seem impossible particularly when undertaken by individual users. However, the advent of Web 2.0 and associated communities, such as YouTube and Flickr, has
shown that users appear to be more willing to collaborate in order to take on enormous tasks such as multimedia content modelling. Harnessing the power of communities to achieve comprehensive content modelling is the primary focus of this research.
The aim of this thesis is to explore collaborative multimedia content modelling and in particular the effectiveness of existing multimedia content modelling tools, taking into account the key development challenges of existing collaborative content modelling research and the associated
modelling tools. Four research objectives are pursued in order to achieve this; first, design a user experiment to study users’ tagging behaviour with existing multimedia tagging tools and identify any relationships between such user behaviour; second, design and develop a framework for MPEG-7 content modelling communities based on the results of the experiment; third, implement an online
service as a proof of concept of the framework; fourth, validate the framework through the online service during a repeat of the initial user experiment.
This research contributes first, a conceptual model of user behaviour visualised as a fuzzy cognitive
map and, second, an MPEG-7 framework for multimedia content modelling communities (MC2) and its proof of concept as an online service. The fuzzy cognitive model embodies relationships between user tagging behaviour and context and provides an understanding of user priorities in the description of content features and the relationships that exist between them. The MC2 framework,
developed based on the fuzzy cognitive model, is deep-rooted in user content modelling behaviour and content preferences. A proof of concept of the MC2 framework is implemented as an online service in which all metadata is modelled using MPEG-7. The online service is validated, first, empirically with the same group of users and through the same experiment that led to the development of the fuzzy cognitive model and, second, functionally against the folksonomy and MPEG-7 content modelling tools used in the initial experiment. The validation demonstrates that MC2 has the advantages without the shortcomings of existing multimedia tagging tools by harnessing the ease of use of folksonomy tools while producing comprehensive structured metadata.Supported by UK Engineering and Physical Sciences Research Council (EPSRC
The gamification of accessibility design: A proposed framework
The use of Gamification for the purpose of training and raising awareness has attracted considerable interest over the last years. However, the development of such solutions to use within the area of accessibility design has not been yet explored. In this paper, we present a proposed framework using Gamification as a method for engaging and motivating web designers to increase the adoption of the W3C WCAG 2.0 guidelines. It is anticipated that our framework will provide a more interactive and intuitive learning experience
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Chain of command in autonomous cooperative agents for battles in real-time strategy games
This paper investigates incorporating chain of command in swarm intelligence of honey bees to create groups of ranked co-operative autonomous agents for an RTS game in to create and re-enact battle simulations. The behaviour of the agents are based on the foraging and defensive behaviours of honey bees, adapted to a human environment. The chain of command is implemented using a hierarchical decision model. The groups consist of multiple model-based reflex agents, with individual blackboards for working memory, with a colony level blackboard to mimic the foraging patterns and include commands received from ranking agents. An agent architecture and environment are proposed that allows for creation of autonomous cooperative agents. The behaviour of agents is then evaluated both mathematically and empirically using an adaptation of anytime universal intelligence test and agent believability metric
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A Serious Game for Raising Designer Awareness of Web Accessibility Guidelines
Accessibility of products and services is key for people living with a disability to ensure that they are easier to use. However, web accessibility guidelines have been shown to be cumbersome to understand, which impacts on designers’ intention to use them. Several tools have been proposed in the literature, but they mostly focus on automatic accessibility testing, a process that is performed after a product has been developed. Little attention has been paid to using web accessibility guidelines during the design phase. In this paper, we present GATE, a serious game to help raise designer awareness of web accessibility guidelines, which is part of our work in progress on gamified technologies for this purpose. Its usability and perceived effectiveness were evaluated through an empirical study using a mixed methods approach. Our initial findings show that GATE is a promising solution that scored high in its playability and potential for use. This work has important potential contributions for the wider adoption of web accessibility guidelines
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Swarm intelligence for autonomous cooperative agents in battles for real-time strategy games
This paper investigates the use the swarm intelligence of honey bees to create groups of co-operative AI for an RTS game in order to create and re-enact battle simulations. The behaviour of the agents are based on the foraging and defensive behaviours of honey bees, adapted to a human environment. The groups consist of multiple model-based reflex agents, with individual blackboards for working memory, with a colony level blackboard to mimic the foraging patterns. An agent architecture and environment is proposed that allows for creation of autonomous cooperative agents. The behaviour of agents is then evaluated and their intelligence is tested using an adaptation of Anytime Universal Intelligence Test
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A novel approach to automatic music composing: Using genetic algorithm
Artificial music composition is one of the ever rising problems of computer science. Genetic Algorithm has been one of the most useful means in our hands to solve optimization problems. By use of precise assumptions and adequate fitness function it is possible to change the music composing into an optimization problem. This paper proposes a new genetic algorithm for composing music. Considering entropy of the notes distribution as a factor of fitness function and developing mutation and crossover functions based on harmonic rules and trying to keep the melodies intact during these processes would result in a musical piece pleasant to human ears and interesting for human mind. This algorithm does not have the constraints of the previous algorithms. Restraining mutation and crossover functions with a goal of producing melodies based on acceptable melodies composed by humans, this algorithm is not bound to any genre, instrument or melody. The experimental results of this approach show that it is near to the human composing and the results produced from it are more acceptable than the ones produced by its predecessors
Efficient in-game communication in collaborative online multiplayer Games
The ability to communicate during online gaming is one that has become fundamental. Players could use voice, textual chat, pre-determined commands or a combination of these methods in order to command a team, follow an appointed leader or simply to socialise with friends. There is an abundance of reasons why a person will choose to utilise the conversational frameworks available, however, when considering a game where players must work together in order to reach a common goal, it is up for interpretation to determine which method works most efficiently. The aim of this work is to address this need through a game that utilises these three methods of communication in order to determine their efficiency. A combination of qualitative and quantitative methods was employed to formulate a well-rounded conclusion. Results indicated that a combination of voice and predetermined commands is the most efficient method of in-game communication in online, task-oriented games
A multisensory 3D environment as intervention to aid reading in dyslexia: A proposed framework
Developmental Dyslexia (DD) is a common language-based learning difficulty which occurs across all cultures. Whilst various interventions are implemented to aid with reading difficulties, research suggests that phonics is still the most promising approach, yet the challenge in this approach has always been keeping pupils engaged and interested. Multisensory approaches have shown promise in keeping pupils engaged but they are time consuming and require high levels of teacher involvement. This paper suggests using 3D environments and gaming technology as a multisensory intervention to aid reading in Dyslexia. The paper proposes an initial framework and indicates the development and evaluation strategy for the framework
Lu-Lu: A framework for collaborative decision making games
This paper proposes Lu-Lu as an add-on architecture to open MMOGs and social network games, which has been developed to utilise a key set of ingredients that underline collaborative decision making games as reported within the research literature: personalisation, team matching, non-optimal decision making, leading, decisiveness index, scoring, levelling, and multiple stages. The implementation of Lu-Lu is demonstrated as an add-on to the classic supply chain beer game, including customisation of Lu-Lu to facilitate information exchange through the Facebook games platform, e.g., Graph API and Scores API. Performance assessment of Lu-Lu using Behaviour-Driven Development suggests a successful integration of all key ingredients within Lu-Lu's architecture, yielding autonomous behaviour that improves both player enjoyment and decision making
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Semantic content filtering using self-organizing neural networks
OSMOS-7 is an application that can create and filter MPEG-7 semantic content models with regards to objects and events, both spatially and temporally. The results are presented as numerous video segments that are all relevant to the user's consumption criteria, yet these results are not ranked according to the user's preferences. Using self organizing networks (SONNs) we rank the segments to the user's preferences by applying the knowledge gained from similar users' experience and use content similarity for new segments to derive a relative ranking. To bridge the gap between the user preferences and the content model, an MPEG- 7 model is proposed that uses the hanging basket model to better relate the users 'preferences and usage history to the content