Dynamic Features for Iris Recognition

The human eye is sensitive to visible light. Increasing illumination on the eye causes the pupil of the eye to contract, while decreasing illumination causes the pupil to dilate. Visible light causes specular reflections inside the iris ring. On the other hand, the human retina is less sensitive to near infra-red (NIR) radiation in the wavelength range from 800 nm to 1400 nm, but iris detail can still be imaged with NIR illumination. In order to measure the dynamic movement of the human pupil and iris while keeping the light-induced reflexes from affecting the quality of the digitalized image, this paper describes a device based on the consensual reflex. This biological phenomenon contracts and dilates the two pupils synchronously when illuminating one of the eyes by visible light. In this paper, we propose to capture images of the pupil of one eye using NIR illumination while illuminating the other eye using a visible-light pulse. This new approach extracts iris features called "dynamic features (DFs)." This innovative methodology proposes the extraction of information about the way the human eye reacts to light, and to use such information for biometric recognition purposes. The results demonstrate that these features are discriminating features, and, even using the Euclidean distance measure, an average accuracy of recognition of 99.1% was obtained. The proposed methodology has the potential to be "fraud-proof," because these DFs can only be extracted from living irises.

Influence of texture on the recrystallization mechanisms in an AZ31 Mg sheet alloy at dynamic rates

An AZ31 rolled sheet alloy has been tested at dynamic strain rates View the MathML source at 250 °C up to various intermediate strains before failure in order to investigate the predominant deformation and restoration mechanisms. In particular, tests have been carried out in compression along the rolling direction (RD), in tension along the RD and in compression along the normal direction (ND). It has been found that dynamic recrystallization (DRX) takes place despite the limited diffusion taking place under the high strain rates investigated. The DRX mechanisms and kinetics depend on the operative deformation mechanisms and thus vary for different loading modes (tension, compression) as well as for different relative orientations between the loading axis and the c-axes of the grains. In particular, DRX is enhanced by the operation of 〈c + a〉 slip, since cross-slip and climb take place more readily than for other slip systems, and thus the formation of high angle boundaries is easier. DRX is also clearly promoted by twinning.

Progressive structural analysis for dynamic recognition of on-line handwritten mathematical expressions

Structural analysis in handwritten mathematical expressions focuses on interpreting the recognized symbols using geometrical information such as relative sizes and positions of the symbols. Most existing approaches rely on hand-crafted grammar rules to identify semantic relationships among the recognized mathematical symbols. They could easily fail when writing errors occurred. Moreover, they assume the availability of the whole mathematical expression before being able to analyze the semantic information of the expression. To tackle these problems, we propose a progressive structural analysis (PSA) approach for dynamic recognition of handwritten mathematical expressions. The proposed PSA approach is able to provide analysis result immediately after each written input symbol. This has an advantage that users are able to detect any recognition errors immediately and correct only the mis-recognized symbols rather than the whole expression. Experiments conducted on 57 most commonly used mathematical expressions have shown that the PSA approach is able to achieve very good performance results.

Emotion recognition from dynamic emotional displays following anterior cingulotomy and anterior capsulotomy for chronic depression

Four patients that had received an anterior cingulotomy (ACING) and five patients that had received both an ACING and an anterior capsulotomy (ACAPS) as an intervention for chronic, treatment refractory depression were presented with a series of dynamic emotional stimuli and invited to identify the emotion portrayed. Their performance was compared with that of a group of non-surgically treated patients with major depression (n = 17) and with a group of matched, never-depressed controls (n = 22). At the time of testing, four of the nine neurosurgery patients had recovered from their depressive episode, whereas five remained depressed. Analysis of emotion recognition accuracy revealed no significant differences between depressed and non-depressed neurosurgically treated patients. Similarly, no significant differences were observed between the patients treated with ACING alone and those treated with both ACING and ACAPS. Comparison of the emotion recognition accuracy of the neurosurgically treated patients and the depressed and healthy control groups revealed that the surgically treated patients exhibited a general impairment in their recognition accuracy compared to healthy controls. Regression analysis revealed that participants' emotion recognition accuracy was predicted by the number of errors they made on the Stroop colour-naming task. It is plausible that the observed deficit in emotion recognition accuracy was a consequence of impaired attentional control, which may have been a result of the surgical lesions to the anterior cingulate cortex. © 2007 Elsevier Ltd. All rights reserved.

Normal ECG Recognition for Express-Diagnostics Based on Scale-Space Representation and Dynamic Matching

A novel approach of normal ECG recognition based on scale-space signal representation is proposed. The approach utilizes curvature scale-space signal representation used to match visual objects shapes previously and dynamic programming algorithm for matching CSS representations of ECG signals. Extraction and matching processes are fast and experimental results show that the approach is quite robust for preliminary normal ECG recognition.

Dynamic Distance-Based Shape Features for Gait Recognition

We propose a novel skeleton-based approach to gait recognition using our Skeleton Variance Image. The core of our approach consists of employing the screened Poisson equation to construct a family of smooth distance functions associated with a given shape. The screened Poisson distance function approximation nicely absorbs and is relatively stable to shape boundary perturbations which allows us to define a rough shape skeleton. We demonstrate how our Skeleton Variance Image is a powerful gait cycle descriptor leading to a significant improvement over the existing state of the art gait recognition rate.

Evaluating Dynamic Signage for Emergency Evacuation using an Immersive Video Environment

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Bacterial peptidoglycan biosynthesis and recognition by the innate immune system

Dissertation presented to obtain the Ph.D degree in Biology

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Object recognition for autonomous objects: comparison of two approaches

Report for the scientific sojourn at the Swiss Federal Institute of Technology Zurich, Switzerland, between September and December 2007. In order to make robots useful assistants for our everyday life, the ability to learn and recognize objects is of essential importance. However, object recognition in real scenes is one of the most challenging problems in computer vision, as it is necessary to deal with difficulties. Furthermore, in mobile robotics a new challenge is added to the list: computational complexity. In a dynamic world, information about the objects in the scene can become obsolete before it is ready to be used if the detection algorithm is not fast enough. Two recent object recognition techniques have achieved notable results: the constellation approach proposed by Lowe and the bag of words approach proposed by Nistér and Stewénius. The Lowe constellation approach is the one currently being used in the robot localization project of the COGNIRON project. This report is divided in two main sections. The first section is devoted to briefly review the currently used object recognition system, the Lowe approach, and bring to light the drawbacks found for object recognition in the context of indoor mobile robot navigation. Additionally the proposed improvements for the algorithm are described. In the second section the alternative bag of words method is reviewed, as well as several experiments conducted to evaluate its performance with our own object databases. Furthermore, some modifications to the original algorithm to make it suitable for object detection in unsegmented images are proposed.

An exploratory study on facial emotion recognition capacity in beginning Alzheimer's disease.

Objective: It was the aim of this study to investigate facial emotion recognition (FER) in the elderly with cognitive impairment. Method: Twelve patients with Alzheimer's disease (AD) and 12 healthy control subjects were asked to name dynamic or static pictures of basic facial emotions using the Multimodal Emotion Recognition Test and to assess the degree of their difficulty in the recognition task, while their electrodermal conductance was registered as an unconscious processing measure. Results: AD patients had lower objective recognition performances for disgust and fear, but only disgust was accompanied by decreased subjective FER in AD patients. The electrodermal response was similar in all groups. No significant effect of dynamic versus static emotion presentation on FER was found. Conclusion: Selective impairment in recognizing facial expressions of disgust and fear may indicate a nonlinear decline in FER capacity with increasing cognitive impairment and result from progressive though specific damage to neural structures engaged in emotional processing and facial emotion identification. Although our results suggest unchanged unconscious FER processing with increasing cognitive impairment, further investigations on unconscious FER and self-awareness of FER capacity in neurodegenerative disorders are required.

Identity, immigration, and prejudice in Europe: a recognition approach

Social identity is a double-edged sword. On the one hand, identifying with a social group is a prerequisite for the sharing of common norms and values, solidarity, and collective action. On the other hand, in-group identification often goes together with prejudice and discrimination. Today, these two sides of social identification underlie contradictory trends in the way European nations and European nationals relate to immigrants and immigration. Most European countries are becoming increasingly multicultural, and anti-discrimination laws have been adopted throughout the European Union, demonstrating a normative shift towards more social inclusion and tolerance. At the same time, racist and xenophobic attitudes still shape social relations, individual as well as collective behaviour (both informal and institutional), and political positions throughout Europe. The starting point for this chapter is Sanchez-Mazas' (2004) interactionist approach to the study of racism and xenophobia, which in turn builds on Axel Honneth's (1996) philosophical theory of recognition. In this view, the origin of attitudes towards immigrants cannot be located in one or the other group, but in a dynamic of mutual influence. Sanchez-Mazas' approach is used as a general framework into which we integrate social psychological approaches of prejudice and recent empirical findings examining minority-majority relations. We particularly focus on the role of national and European identities as antecedents of anti-immigrant attitudes held by national majorities. Minorities' reactions to denials of recognition are also examined. We conclude by delineating possible social and political responses to prejudice towards immigrants.

Increased mobility of major histocompatibility complex I-peptide complexes decreases the sensitivity of antigen recognition.

CD8(+) cytotoxic T lymphocytes (CTL) can recognize and kill target cells expressing only a few cognate major histocompatibility complex (MHC) I-peptide complexes. This high sensitivity requires efficient scanning of a vast number of highly diverse MHC I-peptide complexes by the T cell receptor in the contact site of transient conjugates formed mainly by nonspecific interactions of ICAM-1 and LFA-1. Tracking of single H-2K(d) molecules loaded with fluorescent peptides on target cells and nascent conjugates with CTL showed dynamic transitions between states of free diffusion and immobility. The immobilizations were explained by association of MHC I-peptide complexes with ICAM-1 and strongly increased their local concentration in cell adhesion sites and hence their scanning by T cell receptor. In nascent immunological synapses cognate complexes became immobile, whereas noncognate ones diffused out again. Interfering with this mobility modulation-based concentration and sorting of MHC I-peptide complexes strongly impaired the sensitivity of antigen recognition by CTL, demonstrating that it constitutes a new basic aspect of antigen presentation by MHC I molecules.

3D seismic facies characterization and geological patterns recognition (Australian North West Shelf)

EXECUTIVE SUMMARY This PhD research, funded by the Swiss Sciences Foundation, is principally devoted to enhance the recognition, the visualisation and the characterization of geobodies through innovative 3D seismic approaches. A series of case studies from the Australian North West Shelf ensures the development of reproducible integrated 3D workflows and gives new insight into local and regional stratigraphic as well as structural issues. This project was initiated in year 2000 at the Geology and Palaeontology Institute of the University of Lausanne (Switzerland). Several collaborations ensured the improvement of technical approaches as well as the assessment of geological models. - Investigations into the Timor Sea structural style were carried out at the Tectonics Special Research Centre of the University of Western Australia and in collaboration with Woodside Energy in Perth. - Seismic analysis and attributes classification approach were initiated with Schlumberger Oilfield Australia in Perth; assessments and enhancements of the integrated seismic approaches benefited from collaborations with scientists from Schlumberger Stavanger Research (Norway). Adapting and refining from "linear" exploration techniques, a conceptual "helical" 3D seismic approach has been developed. In order to investigate specific geological issues this approach, integrating seismic attributes and visualisation tools, has been refined and adjusted leading to the development of two specific workflows: - A stratigraphic workflow focused on the recognition of geobodies and the characterization of depositional systems. Additionally, it can support the modelling of the subsidence and incidentally the constraint of the hydrocarbon maturity of a given area. - A structural workflow used to quickly and accurately define major and secondary fault systems. The integration of the 3D structural interpretation results ensures the analysis of the fault networks kinematics which can affect hydrocarbon trapping mechanisms. The application of these integrated workflows brings new insight into two complex settings on the Australian North West Shelf and ensures the definition of astonishing stratigraphic and structural outcomes. The stratigraphic workflow ensures the 3D characterization of the Late Palaeozoic glacial depositional system on the Mermaid Nose (Dampier Subbasin, Northern Carnarvon Basin) that presents similarities with the glacial facies along the Neotethys margin up to Oman (chapter 3.1). A subsidence model reveals the Phanerozoic geodynamic evolution of this area (chapter 3.2) and emphasizes two distinct mode of regional extension for the Palaeozoic (Neotethys opening) and Mesozoic (abyssal plains opening). The structural workflow is used for the definition of the structural evolution of the Laminaria High area (Bonaparte Basin). Following a regional structural characterization of the Timor Sea (chapter 4.1), a thorough analysis of the Mesozoic fault architecture reveals a local rotation of the stress field and the development of reverse structures (flower structures) in extensional setting, that form potential hydrocarbon traps (chapter 4.2). The definition of the complex Neogene structural architecture associated with the fault kinematic analysis and a plate flexure model (chapter 4.3) suggest that the Miocene to Pleistocene reactivation phases recorded at the Laminaria High most probably result from the oblique normal reactivation of the underlying Mesozoic fault planes. This episode is associated with the deformation of the subducting Australian plate. Based on these results three papers were published in international journals and two additional publications will be submitted. Additionally this research led to several communications in international conferences. Although the different workflows presented in this research have been primarily developed and used for the analysis of specific stratigraphic and structural geobodies on the Australian North West Shelf, similar integrated 3D seismic approaches will have applications to hydrocarbon exploration and production phases; for instance increasing the recognition of potential source rocks, secondary migration pathways, additional traps or reservoir breaching mechanisms. The new elements brought by this research further highlight that 3D seismic data contains a tremendous amount of hidden geological information waiting to be revealed and that will undoubtedly bring new insight into depositional systems, structural evolution and geohistory of the areas reputed being explored and constrained and other yet to be constrained. The further development of 3D texture attributes highlighting specific features of the seismic signal, the integration of quantitative analysis for stratigraphic and structural processes, the automation of the interpretation workflow as well as the formal definition of "seismo-morphologic" characteristics of a wide range of geobodies from various environments would represent challenging examples of continuation of this present research. The 21st century will most probably represent a transition period between fossil and other alternative energies. The next generation of seismic interpreters prospecting for hydrocarbon will undoubtedly face new challenges mostly due to the shortage of obvious and easy targets. They will probably have to keep on integrating techniques and geological processes in order to further capitalise the seismic data for new potentials definition. Imagination and creativity will most certainly be among the most important quality required from such geoscientists.

Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition

Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques