“It puts a human face on the researched”: A qualitative evaluation of an Indigenous research governance model

Objective This study aimed to describe the Inala Aboriginal and Torres Strait Islander Community Jury for Health Research, and evaluate its usefulness as a model of Indigenous research governance within an urban Indigenous primary health care service from the perspectives of Jury members and researchers. Methods Informed by a phenomenological approach and using narrative inquiry, a focus group was conducted with Jury members and key informant interviews were undertaken with researchers who had presented to the Community Jury in its first year of operation. Results The Jury was a site of identity work for researchers and Jury members, providing an opportunity to observe and affirm community cultural protocols. Although researchers and Jury members had differing levels of research literacy, the Jury processes enabled respectful communication and relationships to form which positively influenced research practice, community aspirations and clinical care. Discussion The Jury processes facilitated transformative research practice among researchers, and resulted in transference of power from researchers to the Jury members to the mutual benefit of both. Conclusion Ethical Indigenous health research practice requires an engagement with Indigenous peoples and knowledges at the research governance level, not simply as subjects or objects of research.

Social perception and cognition : processing of gestures, postures and facial expressions in the human brain

Humans are a social species with the internal capability to process social information from other humans. To understand others behavior and to react accordingly, it is necessary to infer their internal states, emotions and aims, which are conveyed by subtle nonverbal bodily cues such as postures, gestures, and facial expressions. This thesis investigates the brain functions underlying the processing of such social information. Studies I and II of this thesis explore the neural basis of perceiving pain from another person s facial expressions by means of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG). In Study I, observing another s facial expression of pain activated the affective pain system (previously associated with self-experienced pain) in accordance with the intensity of the observed expression. The strength of the response in anterior insula was also linked to the observer s empathic abilities. The cortical processing of facial pain expressions advanced from the visual to temporal-lobe areas at similar latencies (around 300 500 ms) to those previously shown for emotional expressions such as fear or disgust. Study III shows that perceiving a yawning face is associated with middle and posterior STS activity, and the contagiousness of a yawn correlates negatively with amygdalar activity. Study IV explored the brain correlates of interpreting social interaction between two members of the same species, in this case human and canine. Observing interaction engaged brain activity in very similar manner for both species. Moreover, the body and object sensitive brain areas of dog experts differentiated interaction from noninteraction in both humans and dogs whereas in the control subjects, similar differentiation occurred only for humans. Finally, Study V shows the engagement of the brain area associated with biological motion when exposed to the sounds produced by a single human being walking. However, more complex pattern of activation, with the walking sounds of several persons, suggests that as the social situation becomes more complex so does the brain response. Taken together, these studies demonstrate the roles of distinct cortical and subcortical brain regions in the perception and sharing of others internal states via facial and bodily gestures, and the connection of brain responses to behavioral attributes.

Robust automatic face clustering in news video

Clustering identities in a video is a useful task to aid in video search, annotation and retrieval, and cast identification. However, reliably clustering faces across multiple videos is challenging task due to variations in the appearance of the faces, as videos are captured in an uncontrolled environment. A person's appearance may vary due to session variations including: lighting and background changes, occlusions, changes in expression and make up. In this paper we propose the novel Local Total Variability Modelling (Local TVM) approach to cluster faces across a news video corpus; and incorporate this into a novel two stage video clustering system. We first cluster faces within a single video using colour, spatial and temporal cues; after which we use face track modelling and hierarchical agglomerative clustering to cluster faces across the entire corpus. We compare different face recognition approaches within this framework. Experiments on a news video database show that the Local TVM technique is able effectively model the session variation observed in the data, resulting in improved clustering performance, with much greater computational efficiency than other methods.

A Profilometric Approach to 3D Face Reconstruction and Its Application to Face Recognition

3D Face Recognition is an active area of research for past several years. For a 3D face recognition system one would like to have an accurate as well as low cost setup for constructing 3D face model. In this paper, we use Profilometry approach to obtain a 3D face model.This method gives a low cost solution to the problem of acquiring 3D data and the 3D face models generated by this method are sufficiently accurate. We also develop an algorithm that can use the 3D face model generated by the above method for the recognition purpose.

Contributions to unsupervised and supervised learning with applications in digital image processing

311 p. : il.

Research of Face Detection System Applied for Detecting Faces with Complex Background and Illumination

An effective face detection system used for detecting multi pose frontal face in gray images is presented. Image preprocessing approaches are applied to reduce the influence of the complex illumination. Eye-analog pairing and improved multiple related template matching are used to glancing and accurate face detecting, respectively. To shorten the time cost of detecting process, we employ prejudge rules in checking candidate image segments before template matching. Test by our own face database with complicated illumination and background, the system has high calculation speed and illumination independency, and obtains good experimental results.

Research of Face Location System Based on Human Vision Simulations

In this paper we present a robust face location system based on human vision simulations to automatically locate faces in color static images. Our method is divided into four stages. In the first stage we use a gauss low-pass filter to remove the fine information of images, which is useless in the initial stage of human vision. During the second and the third stages, our technique approximately detects the image regions, which may contain faces. During the fourth stage, the existence of faces in the selected regions is verified. Having combined the advantages of Bottom-Up Feature Based Methods and Appearance-Based Methods, our algorithm performs well in various images, including those with highly complex backgrounds.

Architecture research and hardware implementation on simplified neural computing system for face identification

This paper describes a special-purpose neural computing system for face identification. The system architecture and hardware implementation are introduced in detail. An algorithm based on biomimetic pattern recognition has been embedded. For the total 1200 tests for face identification, the false rejection rate is 3.7% and the false acceptance rate is 0.7%.

Research and perspectives on processing instruction

This volume tracks the impact processing instruction has made since its conception. It provides an overview of new research trends on measuring the relative effects of processing instruction. Firstly, the authors explain processing instruction, both its main theoretical underpinnings as well as the guidelines for developing structured input practices. Secondly, they review the empirical research conducted, to date, so that readers have an overview of new research carried out on the effects of processing instruction. The authors finally reflect on the generalizability and limits of the research on processing instruction and offer future directions for processing instruction research.

Image, Video and 3D Data Registration: Medical, Satellite and Video Processing Applications with Quality Metrics

Data registration refers to a series of techniques for matching or bringing similar objects or datasets together into alignment. These techniques enjoy widespread use in a diverse variety of applications, such as video coding, tracking, object and face detection and recognition, surveillance and satellite imaging, medical image analysis and structure from motion. Registration methods are as numerous as their manifold uses, from pixel level and block or feature based methods to Fourier domain methods.

This book is focused on providing algorithms and image and video techniques for registration and quality performance metrics. The authors provide various assessment metrics for measuring registration quality alongside analyses of registration techniques, introducing and explaining both familiar and state-of-the-art registration methodologies used in a variety of targeted applications.

Key features:
- Provides a state-of-the-art review of image and video registration techniques, allowing readers to develop an understanding of how well the techniques perform by using specific quality assessment criteria
- Addresses a range of applications from familiar image and video processing domains to satellite and medical imaging among others, enabling readers to discover novel methodologies with utility in their own research
- Discusses quality evaluation metrics for each application domain with an interdisciplinary approach from different research perspectives

Alexithymia, emotional processing and psychotherapy : a mixed methods research

Tese de doutoramento, Psicologia (Psicologia Clínica), Universidade de Lisboa, Faculdade de Psicologia, 2014