Tensor regression based on linked multiway parameter analysis

Classical regression methods take vectors as covariates and estimate the corresponding vectors of regression parameters. When addressing regression problems on covariates of more complex form such as multi-dimensional arrays (i.e. tensors), traditional computational models can be severely compromised by ultrahigh dimensionality as well as complex structure. By exploiting the special structure of tensor covariates, the tensor regression model provides a promising solution to reduce the model’s dimensionality to a manageable level, thus leading to efficient estimation. Most of the existing tensor-based methods independently estimate each individual regression problem based on tensor decomposition which allows the simultaneous projections of an input tensor to more than one direction along each mode. As a matter of fact, multi-dimensional data are collected under the same or very similar conditions, so that data share some common latent components but can also have their own independent parameters for each regression task. Therefore, it is beneficial to analyse regression parameters among all the regressions in a linked way. In this paper, we propose a tensor regression model based on Tucker Decomposition, which identifies not only the common components of parameters across all the regression tasks, but also independent factors contributing to each particular regression task simultaneously. Under this paradigm, the number of independent parameters along each mode is constrained by a sparsity-preserving regulariser. Linked multiway parameter analysis and sparsity modeling further reduce the total number of parameters, with lower memory cost than their tensor-based counterparts. The effectiveness of the new method is demonstrated on real data sets

Tensor Representations for Object Classification and Detection

A key problem in object recognition is finding a suitable object representation. For historical and computational reasons, vector descriptions that encode particular statistical properties of the data have been broadly applied. However, employing tensor representation can describe the interactions of multiple factors inherent to image formation. One of the most convenient uses for tensors is to represent complex objects in order to build a discriminative description. Thus thesis has several main contributions, focusing on visual data detection (e.g. of heads or pedestrians) and classification (e.g. of head or human body orientation) in still images and on machine learning techniques to analyse tensor data. These applications are among the most studied in computer vision and are typically formulated as binary or multi-class classification problems. The applicative context of this thesis is the video surveillance, where classification and detection tasks can be very hard, due to the scarce resolution and the noise characterising sensor data. Therefore, the main goal in that context is to design algorithms that can characterise different objects of interest, especially when immersed in a cluttered background and captured at low resolution. In the different amount of machine learning approaches, the ensemble-of-classifiers demonstrated to reach excellent classification accuracy, good generalisation ability, and robustness of noisy data. For these reasons, some approaches in that class have been adopted as basic machine classification frameworks to build robust classifiers and detectors. Moreover, also kernel machines has been exploited for classification purposes, since they represent a natural learning framework for tensors

Low Latency Rendering with Dataflow Architectures

The research presented in this thesis concerns latency in VR and synthetic environments. Latency is the end-to-end delay experienced by the user of an interactive computer system, between their physical actions and the perceived response to these actions. Latency is a product of the various processing, transport and buffering delays present in any current computer system. For many computer mediated applications, latency can be distracting, but it is not critical to the utility of the application. Synthetic environments on the other hand attempt to facilitate direct interaction with a digitised world. Direct interaction here implies the formation of a sensorimotor loop between the user and the digitised world - that is, the user makes predictions about how their actions affect the world, and see these predictions realised. By facilitating the formation of the this loop, the synthetic environment allows users to directly sense the digitised world, rather than the interface, and induce perceptions, such as that of the digital world existing as a distinct physical place. This has many applications for knowledge transfer and efficient interaction through the use of enhanced communication cues. The complication is, the formation of the sensorimotor loop that underpins this is highly dependent on the fidelity of the virtual stimuli, including latency. The main research questions we ask are how can the characteristics of dataflow computing be leveraged to improve the temporal fidelity of the visual stimuli, and what implications does this have on other aspects of the fidelity. Secondarily, we ask what effects latency itself has on user interaction. We test the effects of latency on physical interaction at levels previously hypothesized but unexplored. We also test for a previously unconsidered effect of latency on higher level cognitive functions. To do this, we create prototype image generators for interactive systems and virtual reality, using dataflow computing platforms. We integrate these into real interactive systems to gain practical experience of how the real perceptible benefits of alternative rendering approaches, but also what implications are when they are subject to the constraints of real systems. We quantify the differences of our systems compared with traditional systems using latency and objective image fidelity measures. We use our novel systems to perform user studies into the effects of latency. Our high performance apparatuses allow experimentation at latencies lower than previously tested in comparable studies. The low latency apparatuses are designed to minimise what is currently the largest delay in traditional rendering pipelines and we find that the approach is successful in this respect. Our 3D low latency apparatus achieves lower latencies and higher fidelities than traditional systems. The conditions under which it can do this are highly constrained however. We do not foresee dataflow computing shouldering the bulk of the rendering workload in the future but rather facilitating the augmentation of the traditional pipeline with a very high speed local loop. This may be an image distortion stage or otherwise. Our latency experiments revealed that many predictions about the effects of low latency should be re-evaluated and experimenting in this range requires great care

Evaluating the Perceived Quality of Binaural Technology

This thesis studies binaural sound reproduction from both a technical and a perceptual perspective, with the aim of improving the headphone listening experience for entertainment media audiences. A detailed review is presented of the relevant binaural technology and of the concepts and methods for evaluating perceived quality. A pilot study assesses the application of state-of-the-art binaural rendering systems to existing broadcast programmes, finding no substantial improvements in quality over conventional stereo signals. A second study gives evidence that realistic binaural simulation can be achieved without personalised acoustic calibration, showing promise for the application of binaural technology. Flexible technical apparatus is presented to allow further investigation of rendering techniques and content production processes. Two web-based studies show that appropriate combination of techniques can lead to improved experience for typical audience members, compared to stereo signals, even without personalised rendering or listener head-tracking. Recent developments in spatial audio applications are then discussed. These have made dynamic client-side binaural rendering with listener head-tracking feasible for mass audiences, but also present technical constraints. To limit distribution bandwidth and computational complexity during rendering, loudspeaker virtualisation is widely used. The effects on perceived quality of these techniques are studied in depth for the first time. A descriptive analysis experiment demonstrates that loudspeaker virtualisation during binaural rendering causes degradations to a range of perceptual characteristics and that these vary across other system conditions. A final experiment makes novel use of the check-all-that-apply method to efficiently characterise the quality of seven spatial audio representations and associated dynamic binaural rendering techniques, using single sound sources and complex dramatic scenes. The perceived quality of these different representations varies significantly across a wide range of characteristics and with programme material. These methods and findings can be used to improve the quality of current binaural technology applications

Toward the real time estimation of the attentional state through ocular activity analysis

L'analyse d'incidents aéronautiques et d'expériences en laboratoire a montré que la tunnélisation attentionnelle amène les pilotes à négliger des alarmes critiques. Une piste intéressante pour répondre à ce problème s'appuie sur les systèmes adaptatifs qui pourraient assister l'opérateur en temps réel (en changeant le comportement du pilote automatique par exemple). Ce type de systèmes adaptatifs requiert l'état de l'opérateur en entrée. Pour cela, des méthodes d'inférence de l'état de l'opérateur doublées de métriques de la tunnélisation attentionnelle doivent être proposées. Le but de cette thèse de doctorat est d'apporter la preuve que la détection de la tunnélisation attentionnelle est possible en temps réel. Pour cela une méthode adaptative neuro-floue utilisant les métriques de la tunnélisation attentionnelle sera proposée, ainsi que de nouvelles métriques de la tunnélisation attentionnelle qui ne dépendent pas du contexte de l'opérateur, et qui sont calculables en temps réel. L'algorithme d'identification des états de l'oeil (ESIA) est proposé en ce sens. Les métriques attentionnelles en sont dérivées et testées dans le contexte d'une expérience robotique dont le design favorise la tunnélisation attentionnellle. Nous proposons également une nouvelle définition du ratio exploitation/exploration d'information dont la pertinence en tant que marqueur de la tunnélisation attentionnelle est démontrée statistiquement. Le travail est ensuite discuté et appliqué sur divers cas d'étude en aviation et robotique.The analysis of aerospace incidents and laboratory experiments have shown that attentional tunneling leads pilots to neglect critical alarms. One interesting avenue to deal with this issue is to consider adaptive systems that would help the operator in real time (for instance: switching the auto-pilot mode). Such adaptive systems require the operator's state as an input. Therefore, both attentional tunneling metrics and state inference techniques have to be proposed. The goal of the PhD Thesis is to provide attentional tunneling metrics that are real-time and context independent. The Eye State Identification Algorithm (ESIA) that analyses ocular activity is proposed. Metrics are then derived and tested on a robotic experiment meant for favouring attentional tunneling. We also propose a new definition of the explore/exploit ratio that was proven statistically to be a relevant attentional tunneling marker. This work is then discussed and applied to different case studies in aviation and robotics

EVALUATION OF MULTIPLE CUE HEAD POSE ESTIMATION ALGORITHMS IN NATURAL ENVIRONEMENTS

{ba,odobez} at idiap dot c

Learning algebra in a computer algebra environment : design research on the understanding of the concept of parameter

It is well known that algebra is a difficult topic in the school mathematics curriculum, and is often experienced as a stumbling-block. One of the directions in which solutions to the problems with the learning of algebra can be sought is the integration of information technology (IT) into mathematics education. Although originally not developed for educational purposes, a computer algebra system is an IT tool that seems promising because of its algebraic power. The basic aim of this study, therefore, is to investigate whether computer algebra use can contribute to the understanding of algebra. This leads to the following main research question: How can the use of computer algebra promote the understanding of algebraic concepts and operations? Chapter 1 contains the research questions and explains the aims and backgrounds of the study. In Chapter 2 the research design and methodology are described. Key words are design research and hypothetical learning trajectory. Chapters 1 and 2 together indicate what the research is about and how it is conducted. Chapters 3, 4 and 5 form the theoretical part of the thesis. They treat the main themes of the study: algebra in general, the concept of parameter in particular and the possible roles of computer algebra. Chapter 3 concerns algebra in general. It sketches different views on algebra and describes the standpoint of this study. The theoretical issues of symbol sense, symbolizing, the process-object duality and Realistic Mathematics Education are addressed. In Chapter 4, we zoom in on the concept of parameter. After a brief historical perspective, a conceptual analysis of the parameter is given. Then we describe what we consider a higher level understanding of the concept of parameter. This is connected to the theoretical notions from Chapter 3. Chapter 5 deals with the tool that students use in this research project: computer algebra. Besides an overview of previous research in this domain, it contains a description of the theory of instrumentation that will be used in Chapter 10 in particular. Chapters 6 - 10 form the empirical part of the dissertation. Chapters 6, 7 and 8 describe the development of the hypothetical learning trajectory and the classroom experiences during the three subsequent research cycles. Chapter 9 concerns the contribution of computer algebra use to the understanding of the concept of parameter. In Chapter 10, the results concerning the instrumentation of computer algebra are presented. Chapter 11, finally, answers the main research question. After that, we look back on the study and discuss the results and the methodology. Also, the relevance of the theoretical framework and the generalizability of the findings are evaluated. The chapter ends with recommendations for teaching, for software design and for further researc