Hybrid Particle and Kalman Filtering for Pupil Tracking in Active IR Illumination Gaze Tracking System

A novel pupil tracking method is proposed by combining particle filtering and Kalman filtering for the fast and accurate detection of pupil target in an active infrared source gaze tracking system. Firstly, we utilize particle filtering to track pupil in synthesis triple-channel color map (STCCM) for the fast detection and develop a comprehensive pupil motion model to conduct and analyze the randomness of pupil motion. Moreover, we built a pupil observational model based on the similarity measurement with generated histogram to improve the credibility of particle weights. Particle filtering can detect pupil region in adjacent frames rapidly. Secondly, we adopted Kalman filtering to estimate the pupil parameters more precisely. The state transitional equation of the Kalman filtering is determined by the particle filtering estimation, and the observation of the Kalman filtering is dependent on the detected pupil parameters in the corresponding region of difference images estimated by particle filtering. Tracking results of Kalman filtering are the final pupil target parameters. Experimental results demonstrated the effectiveness and feasibility of this method.Published versio

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Affect-based information retrieval

One of the main challenges Information Retrieval (IR) systems face nowadays originates from the semantic gap problem: the semantic difference between a user’s query representation and the internal representation of an information item in a collection. The gap is further widened when the user is driven by an ill-defined information need, often the result of an anomaly in his/her current state of knowledge. The formulated search queries, which are submitted to the retrieval systems to locate relevant items, produce poor results that do not address the users’ information needs. To deal with information need uncertainty IR systems have employed in the past a range of feedback techniques, which vary from explicit to implicit. The first category of feedback techniques necessitates the communication of explicit relevance judgments, in return for better query reformulations and recommendations of relevant results. However, the latter happens at the expense of users’ cognitive resources and, furthermore, introduces an additional layer of complexity to the search process. On the other hand, implicit feedback techniques make inferences on what is relevant based on observations of user search behaviour. By doing so, they disengage users from the cognitive burden of document rating and relevance assessments. However, both categories of RF techniques determine topical relevance with respect to the cognitive and situational levels of interaction, failing to acknowledge the importance of emotions in cognition and decision making. In this thesis I investigate the role of emotions in the information seeking process and develop affective feedback techniques for interactive IR. This novel feedback framework aims to aid the search process and facilitate a more natural and meaningful interaction. I develop affective models that determine topical relevance based on information gathered from various sensory channels, and enhance their performance using personalisation techniques. Furthermore, I present an operational video retrieval system that employs affective feedback to enrich user profiles and offers meaningful recommendations of unseen videos. The use of affective feedback as a surrogate for the information need is formalised as the Affective Model of Browsing. This is a cognitive model that motivates the use of evidence extracted from the psycho-somatic mobilisation that occurs during cognitive appraisal. Finally, I address some of the ethical and privacy issues that arise from the social-emotional interaction between users and computer systems. This study involves questionnaire data gathered over three user studies, from 74 participants of different educational background, ethnicity and search experience. The results show that affective feedback is a promising area of research and it can improve many aspects of the information seeking process, such as indexing, ranking and recommendation. Eventually, it may be that relevance inferences obtained from affective models will provide a more robust and personalised form of feedback, which will allow us to deal more effectively with issues such as the semantic gap

Avaliação experimental de sistemas de rastreamento ocular do ponto de vista de ações de apontamento e seleção: um estudo de caso.

O objetivo geral desta dissertação é comparar a usabilidade de dois rastreadores oculares de domínio público (os quais utilizam apenas a imagem capturada por uma webcam convencional) e um rastreador comercial de baixo custo, o Tobii EyeX Controller, dotado de múltiplas câmeras dedicadas, durante a realização de tarefas de apontamento e seleção em um computador desktop. Esta pesquisa tem os seguintes objetivos específicos: (1) adaptar parcialmente a abordagem de avaliação proposta por Queiroz (2001) ao contexto de tarefas de apontamento e seleção via rastreamento ocular; (2) confrontar a natureza das falhas identificadas a partir de indicadores da usabilidade de rastreadores oculares; e (3) verificar quais dos identificadores de desempenho dos rastreadores oculares confrontados influenciam positivamente a satisfação subjetiva do usuário. Concluiu-se que os indicadores de eficiência apresentaram resultados satisfatórios para os rastreadores de domínio público. Concluiu-se também que o indicador da satisfação subjetiva do usuário exibiu os melhores escores para os rastreadores de domínio público.The main objective of this dissertation is to compare the usability of two eyetrackers of the public domain (which use only the image captured by a conventional webcam), and a low-cost commercial eye tracker, the Tobii EyeX Controller, equipped with multiple dedicated cameras, during pick-and-click tasks on a desktop computer. This research has the following specific objectives: (1) to adjust partially the evaluation approach proposed by Queiroz (2001) to the context of pointing and selection tasks via eye-tracking; (2) to compare the nature of the problems identified from usability indicators of eye trackers; and (3) to determine which performance indicators of the confronted eye trackers positively impact on the subjective user satisfaction. It was concluded that the chosen efficiency indicators have shown satisfactory results for public domain eye tracker solutions. It was also concluded that the subjective user satisfaction indicator has shown best scores for public domain eye tracker solutions

An Investigation of Iris Recognition in Unconstrained Environments

Iris biometrics is widely regarded as a reliable and accurate method for personal identification and the continuing advancements in the field have resulted in the technology being widely adopted in recent years and implemented in many different scenarios. Current typical iris biometric deployments, while generally expected to perform well, require a considerable level of co-operation from the system user. Specifically, the physical positioning of the human eye in relation to the iris capture device is a critical factor, which can substantially affect the performance of the overall iris biometric system. The work reported in this study will explore some of the important issues relating to the capture and identification of iris images at varying positions with respect to the capture device, and in particular presents an investigation into the analysis of iris images captured when the gaze angle of a subject is not aligned with the axis of the camera lens. A reliable method of acquiring off-angle iris images will be implemented, together with a study of a database thereby compiled of such images captured methodically. A detailed analysis of these so-called “off-angle” characteristics will be presented, making possible the implementation of new methods whereby significant enhancement of system performance can be achieved. The research carried out in this study suggests that implementing carefully new training methodologies to improve the classification performance can compensate effectively for the problem of off-angle iris images. The research also suggests that acquiring off-angle iris samples during the enrolment process for an iris biometric system and the implementation of the developed training configurations provides an increase in classification performance

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Spatial Displays and Spatial Instruments

The conference proceedings topics are divided into two main areas: (1) issues of spatial and picture perception raised by graphical electronic displays of spatial information; and (2) design questions raised by the practical experience of designers actually defining new spatial instruments for use in new aircraft and spacecraft. Each topic is considered from both a theoretical and an applied direction. Emphasis is placed on discussion of phenomena and determination of design principles