17082505
Designing Biomorphs with an Interactive Genetic Algorithm
We describe an interactive version of the Genetic Algorithm which can be used to evolve Fourier series based \biomorphs." The user plays the role of a binary-valued objective function. The usual Genetic operators of Selection, Mutation, and Crossover are applied normally. We discuss the Interactive Genetic Algorithm's use as a teaching tool and in domains in which measures of utility are di cult or impossible to specify mathematically. We argue that the evolution of biomorphs can be considered an ergonomic design problem, and with the evolution of biomorphs as an example, we argue that a large class of design problems can be cast as \imprecise optimization" and \solved" with Interactive Genetic Algorithms. Thus IGAs can be used for applications that fall somewhere between AI, optimization, and CAD.
5213007
Applying electric field sensing to human-computer interfaces
A non-contact sensor based on the interaction of a person with electric fields for human-computer interface is investigated. Two sensing modes are explored: an external electric field shunted to ground through a human body, and an external electric field transmitted through a human body to stationary receivers. The sensors are low power (milliwatts), high resolution (millimeter) low cost (a few dollars per channel), have low latency (millisecond), high update rate (1 kHz), high immunity to noise (>72 dB), are not affected by clothing, surface texture or reflectivity, and can operate on length scales from microns to meters. Systems incorporating the sensors include a finger mouse, a room that knows the location of its occupant, and people-sensing furniture. Haptic feedback using passive materials is described. Also discussed are empirical and analytical approaches to transform sensor measurements into position information.
14619787
Field Mice: Extracting Hand Geometry from Electric Field Measurements
Several members of a family of techniques called Electric Field Sensing are described. Each sensing technique can be understood as a measurement of the value of a different component in an effective circuit diagram that summarizes all possible current pathways involving the body to be sensed and the sensing electrodes. An analytical model of the sensor response is presented, and then a probabilistic framework for inferring geometrical information from field measurements is described. The inference framework is demonstrated for the cases of a two-dimensional and a three-dimensional mouse.
18320669
Operator and parameter adaptation in genetic algorithms
Abstract Genetic Algorithms are a class of powerful, robust search techniques based on genetic inheritance and the Darwinian metaphor of “Natural Selection”. These algorithms maintain a finite memory of individual points on the search landscape known as the “population”. Members of the population are usually represented as strings written over some fixed alphabet, each of which has a scalar value attached to it reflecting its quality or “fitness”. The search may be seen as the iterative application of a number of operators, such as selection, recombination and mutation, to the population with the aim of producing progressively fitter individuals.These operators are usually static, that is to say that their mechanisms, parameters, and probability of application are fixed at the beginning and constant throughout the run of the algorithm. However, there is an increasing body of evidence that not only is there no single choice of operators which is optimal for all problems, but that in fact the optimal choice of operators for a given problem will be time-variant i.e. it will depend on such factors as the degree of convergence of the population. Based on theoretical and practical approaches, a number of authors have proposed methods of adaptively controlling one or more of the operators, usually invoking some kind of “meta-learning” algorithm, in order to try and improve the performance of the Genetic Algorithm as a function optimiser.In this paper we describe the background to these approaches, and suggest a framework for their classification, based on the learning strategy used to control them, and what facets of the algorithm are susceptible to adaptation. We then review a number of significant pieces of work within the context of this setting, and draw some conclusions about the relative merits of various approaches and promising directions for future work.
14200244
A multi-modal system for the retrieval of semantic video events
A framework for event detection is proposed where events, objects, and other semantic concepts are detected from video using trained classifiers. These classifiers are used to automatically annotate video with semantic labels, which in turn are used to search for new, untrained types of events and semantic concepts. The novelty of the approach lies in the: (1) semi-automatic construction of models of events from feature descriptors and (2) integration of content-based and concept-based querying in the search process. Speech retrieval is independently applied and combined results are produced. Results of applying these to the Search benchmark of the NIST TREC Video track 2001 are reported, and the gained experience and future work are discussed.
45241521
Association Schemes, Superschemes, and Relations Invariant Under Permutation Groups
Abstract An association scheme is the associated scheme of a superscheme iff it is a permutation group scheme. The group and its action are recovered from the Bose-Mesner superalgebra of the superscheme, which is a 'quantised' version of a Krasner (relation) algebra of the second kind.
2262504
Video personalization and summarization system
A video personalization and summarization system is designed and implemented to dynamically generate a personalized video summary. The personalization system adopts the three-tier server-middleware-client architecture in order to select, adapt, and deliver rich media content to the user. The server stores the content sources along with their corresponding MPEG-7 metadata descriptions. These semantic metadata are provided through the use of our VideoAnnEx MPEG-7 video annotation tool. When the user initiates a request for content, the client communicates the user request and usage environment descriptions to the middleware. The middleware is powered by the personalization engine and the content adaptation engine. Our personalization engine includes the VideoSue summarization on usage environment engine that selects the optimal set of desired contents according to user preferences. Afterwards, the adaptation engine performs the required transformations and compositions of the selected contents for the specific usage environment using our VideoEd editing and composition tool. Finally, a personalization and summarization system is demonstrated on the IBM Websphere Portal Server for PCs and pervasive devices.
16182080
Self adaptation of mutation rates in a steady state genetic algorithm
This paper investigates the use of genetically encoded mutation rates within a "steady state" genetic algorithm in order to provide a self-adapting mutation mechanism for incremental evolution. One of the outcomes of this work will be a reduction in the number of parameters required to be set by the operator, thus facilitating the transfer of evolutionary computing techniques into an industrial setting. The NK family of landscapes is used to provide a variety of different problems with known statistical features in order to examine the effects of changing various parameters on the performance of the search. A number of policies are considered for the replacement of members of the population with newly created individuals and recombination of material between parents, and a number of methods of encoding for mutation rate are investigated. Empirical comparisons (using the "best-of current-population" metric) over a range of test problems show that a genetic algorithm incorporating the best "flavour" of the adaptive mutation operator outperformed the same algorithm when using any one of a variety of "standard" fixed mutation rates suggested by other authors.