Development of face recognition: Infancy to early childhood

Perception and recognition of faces are fundamental cognitive abilities that form a basis for our social interactions. Research has investigated face perception using a variety of methodologies across the lifespan. Habituation, novelty preference, and visual paired comparison paradigms are typically used to investigate face perception in young infants. Storybook recognition tasks and eyewitness lineup paradigms are generally used to investigate face perception in young children. These methodologies have introduced systematic differences including the use of linguistic information for children but not infants, greater memory load for children than infants, and longer exposure times to faces for infants than for older children, making comparisons across age difficult. Thus, research investigating infant and child perception of faces using common methods, measures, and stimuli is needed to better understand how face perception develops. According to predictions of the Intersensory Redundancy Hypothesis (IRH; Bahrick & Lickliter, 2000, 2002), in early development, perception of faces is enhanced in unimodal visual (i.e., silent dynamic face) rather than bimodal audiovisual (i.e., dynamic face with synchronous speech) stimulation. The current study investigated the development of face recognition across children of three ages: 5 – 6 months, 18 – 24 months, and 3.5 – 4 years, using the novelty preference paradigm and the same stimuli for all age groups. It also assessed the role of modality (unimodal visual versus bimodal audiovisual) and memory load (low versus high) on face recognition. It was hypothesized that face recognition would improve across age and would be enhanced in unimodal visual stimulation with a low memory load. Results demonstrated a developmental trend (F(2, 90) = 5.00, p = 0.009) with older children showing significantly better recognition of faces than younger children. In contrast to predictions, no differences were found as a function of modality of presentation (bimodal audiovisual versus unimodal visual) or memory load (low versus high). This study was the first to demonstrate a developmental improvement in face recognition from infancy through childhood using common methods, measures and stimuli consistent across age.

Integrated visual perception architecture for robotic clothes perception and manipulation

This thesis proposes a generic visual perception architecture for robotic clothes perception and manipulation. This proposed architecture is fully integrated with a stereo vision system and a dual-arm robot and is able to perform a number of autonomous laundering tasks. Clothes perception and manipulation is a novel research topic in robotics and has experienced rapid development in recent years. Compared to the task of perceiving and manipulating rigid objects, clothes perception and manipulation poses a greater challenge. This can be attributed to two reasons: firstly, deformable clothing requires precise (high-acuity) visual perception and dexterous manipulation; secondly, as clothing approximates a non-rigid 2-manifold in 3-space, that can adopt a quasi-infinite configuration space, the potential variability in the appearance of clothing items makes them difficult to understand, identify uniquely, and interact with by machine. From an applications perspective, and as part of EU CloPeMa project, the integrated visual perception architecture refines a pre-existing clothing manipulation pipeline by completing pre-wash clothes (category) sorting (using single-shot or interactive perception for garment categorisation and manipulation) and post-wash dual-arm flattening. To the best of the author’s knowledge, as investigated in this thesis, the autonomous clothing perception and manipulation solutions presented here were first proposed and reported by the author. All of the reported robot demonstrations in this work follow a perception-manipulation method- ology where visual and tactile feedback (in the form of surface wrinkledness captured by the high accuracy depth sensor i.e. CloPeMa stereo head or the predictive confidence modelled by Gaussian Processing) serve as the halting criteria in the flattening and sorting tasks, respectively. From scientific perspective, the proposed visual perception architecture addresses the above challenges by parsing and grouping 3D clothing configurations hierarchically from low-level curvatures, through mid-level surface shape representations (providing topological descriptions and 3D texture representations), to high-level semantic structures and statistical descriptions. A range of visual features such as Shape Index, Surface Topologies Analysis and Local Binary Patterns have been adapted within this work to parse clothing surfaces and textures and several novel features have been devised, including B-Spline Patches with Locality-Constrained Linear coding, and Topology Spatial Distance to describe and quantify generic landmarks (wrinkles and folds). The essence of this proposed architecture comprises 3D generic surface parsing and interpretation, which is critical to underpinning a number of laundering tasks and has the potential to be extended to other rigid and non-rigid object perception and manipulation tasks. The experimental results presented in this thesis demonstrate that: firstly, the proposed grasp- ing approach achieves on-average 84.7% accuracy; secondly, the proposed flattening approach is able to flatten towels, t-shirts and pants (shorts) within 9 iterations on-average; thirdly, the proposed clothes recognition pipeline can recognise clothes categories from highly wrinkled configurations and advances the state-of-the-art by 36% in terms of classification accuracy, achieving an 83.2% true-positive classification rate when discriminating between five categories of clothes; finally the Gaussian Process based interactive perception approach exhibits a substantial improvement over single-shot perception. Accordingly, this thesis has advanced the state-of-the-art of robot clothes perception and manipulation.

A novel polar-based human face recognition computational model

Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB) spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing.

Spectral peak resolution and speech recognition in quiet: Normal hearing, hearing impaired and cochlear implant listeners

Spectral peak resolution was investigated in normal hearing (NH), hearing impaired (HI), and cochlear implant (CI) listeners. The task involved discriminating between two rippled noise stimuli in which the frequency positions of the log-spaced peaks and valleys were interchanged. The ripple spacing was varied adaptively from 0.13 to 11.31 ripples/octave, and the minimum ripple spacing at which a reversal in peak and trough positions could be detected was determined as the spectral peak resolution threshold for each listener. Spectral peak resolution was best, on average, in NH listeners, poorest in CI listeners, and intermediate for HI listeners. There was a significant relationship between spectral peak resolution and both vowel and consonant recognition in quiet across the three listener groups. The results indicate that the degree of spectral peak resolution required for accurate vowel and consonant recognition in quiet backgrounds is around 4 ripples/octave, and that spectral peak resolution poorer than around 1–2 ripples/octave may result in highly degraded speech recognition. These results suggest that efforts to improve spectral peak resolution for HI and CI users may lead to improved speech recognition

Speech recognition in noise for cochlear implant listeners: Benefits of residual hearing

The purpose of this study was to explore the potential advantages, both theoretical and applied, of preserving low-frequency acoustic hearing in cochlear implant patients. Several hypotheses are presented that predict that residual low-frequency acoustic hearing along with electric stimulation for high frequencies will provide an advantage over traditional long-electrode cochlear implants for the recognition of speech in competing backgrounds. A simulation experiment in normal-hearing subjects demonstrated a clear advantage for preserving low-frequency residual acoustic hearing for speech recognition in a background of other talkers, but not in steady noise. Three subjects with an implanted "short-electrode" cochlear implant and preserved low-frequency acoustic hearing were also tested on speech recognition in the same competing backgrounds and compared to a larger group of traditional cochlear implant users. Each of the three short-electrode subjects performed better than any of the traditional long-electrode implant subjects for speech recognition in a background of other talkers, but not in steady noise, in general agreement with the simulation studies. When compared to a subgroup of traditional implant users matched according to speech recognition ability in quiet, the short-electrode patients showed a 9-dB advantage in the multitalker background. These experiments provide strong preliminary support for retaining residual low-frequency acoustic hearing in cochlear implant patients. The results are consistent with the idea that better perception of voice pitch, which can aid in separating voices in a background of other talkers, was responsible for this advantage.

Benefits of amplification for speech recognition in background noise

The purpose of the present study was to examine the benefits of providing audible speech to listeners with sensorineural hearing loss when the speech is presented in a background noise. Previous studies have shown that when listeners have a severe hearing loss in the higher frequencies, providing audible speech (in a quiet background) to these higher frequencies usually results in no improvement in speech recognition. In the present experiments, speech was presented in a background of multitalker babble to listeners with various severities of hearing loss. The signal was low-pass filtered at numerous cutoff frequencies and speech recognition was measured as additional high-frequency speech information was provided to the hearing-impaired listeners. It was found in all cases, regardless of hearing loss or frequency range, that providing audible speech resulted in an increase in recognition score. The change in recognition as the cutoff frequency was increased, along with the amount of audible speech information in each condition (articulation index), was used to calculate the "efficiency" of providing audible speech. Efficiencies were positive for all degrees of hearing loss. However, the gains in recognition were small, and the maximum score obtained by an listener was low, due to the noise background. An analysis of error patterns showed that due to the limited speech audibility in a noise background, even severely impaired listeners used additional speech audibility in the high frequencies to improve their perception of the "easier" features of speech including voicing

The nature of early self-recognition

In studies of mirror-self-recognition subjects are usually surreptitiously marked on their head, and then presented with a mirror. Scores of studies have established that by 18 to 24 months, children investigate their own head upon seeing the mark in the mirror. Scores of papers have debated what this means. Suggestions range from rich interpretations (e.g., the development of self-awareness) to lean accounts (e.g., the development of proprioceptivevisual matching), and include numerous more moderate proposals (e.g., the development of a concept of one's face). In Study 1, 18-24-monthold toddlers were given the standard test and a novel task in which they were marked on their legs rather than on their face. Toddlers performed equivalently on both tasks, suggesting that passing the test does not rely on information specific to facial features. In Study 2, toddlers were surreptitiously slipped into trouser legs that were prefixed to a highchair. Toddlers failed to retrieve the sticker now that their legs looked different from expectations. This finding, together with the findings from a third study which showed that self-recognition in live video feedback develops later than mirror selfrecognition, suggests that performance is not solely the result of proprioceptive-visual matching.

Parafoveal letter recognition at reduced contrast in normal aging and in patients with risk factors for AMD

Background Patients with early age-related maculopathy ( ARM) do not necessarily show obvious morphological signs or functional impairment. Many have good visual acuity, yet complain of decreased visual performance. The aim of this study was to investigate the aging effects on performance of parafoveal letter recognition at reduced contrast, and defects caused by early ARM and normal fellow eyes of patients with unilateral age-related macular degeneration (nfAMD). Methods Testing of the central visual field (8 radius) was performed by the Macular Mapping Test (MMT) using recognition of letters in 40 parafoveal target locations at four contrast levels (5, 10, 25 and 100%). Effects of aging were investigated in 64 healthy subjects aged 23 to 76 years (CTRL). In addition, 39 eyes (minimum visual acuity of 0.63; 20/30) from 39 patients with either no visible signs of ARM, while the fellow eye had advanced age-related macular degeneration (nfAMD; n=12), or early signs of ARM (eARM; n=27) were examined. Performance was expressed summarily as a ""field score"" (FS). Results Performance in the MMT begins to decline linearly with age in normal subjects from the age of 50 and 54 years on, at 5% and 10% contrast respectively. The differentiation between patients and CTRLs was enhanced if FS at 5% was analyzed along with FS at 10% contrast. In 8/12 patients from group nfAMD and in 18/27 from group eARM, the FS was statistically significantly lower than in the CTRL group in at least one of the lower contrast levels. Conclusion Using parafoveal test locations, a recognition task and diminished contrast increases the chance of early detection of functional defects due to eARM or nfAMD and can differentiate them from those due to aging alone.

Dendritic branching of pyramidal cells in the visual cortex of the nocturnal owl monkey: A fractal analysis

The branching structure of neurones is thought to influence patterns of connectivity and how inputs are integrated within the arbor. Recent studies have revealed a remarkable degree of variation in the branching structure of pyramidal cells in the cerebral cortex of diurnal primates, suggesting regional specialization in neuronal function. Such specialization in pyramidal cell structure may be important for various aspects of visual function, such as object recognition and color processing. To better understand the functional role of regional variation in the pyramidal cell phenotype in visual processing, we determined the complexity of the dendritic branching pattern of pyramidal cells in visual cortex of the nocturnal New World owl monkey. We used the fractal dilation method to quantify the branching structure of pyramidal cells in the primary visual area (V1), the second visual area (V2) and the caudal and rostral subdivisions of inferotemporal cortex (ITc and ITr, respectively), which are often associated with color processing. We found that, as in diurnal monkeys, there was a trend for cells of increasing fractal dimension with progression through these cortical areas. The increasing complexity paralleled a trend for increasing symmetry. That we found a similar trend in both diurnal and nocturnal monkeys suggests that it was a feature of a common anthropoid ancestor.

Perceção visual na avaliação diagnóstica em mamografia: uma revisão sistemática

Introdução – Na avaliação diagnóstica em mamografia, o desempenho do radiologista pode estar sujeito a erros de diagnóstico. Objetivo – Descrever a importância da perceção visual na análise da mamografia, identificando os principais fatores que contribuem para a perceção visual do radiologista e que condicionam a acuidade diagnóstica. Metodologia – Estudo descritivo baseado numa revisão sistemática de literatura através da PubMed e da Science Direct. Foram incluídos 42 artigos que respeitavam, pelo menos, um dos critérios de inclusão no estudo. Para a seleção das referências foi utilizada a metodologia PRISMA, constituída por 4 fases: identificação, seleção preliminar, elegibilidade e estudos incluídos. Resultados – Na avaliação diagnóstica em mamografia, a perceção visual está intimamente relacionada com: 1) diferentes parâmetros visuais e da motilidade ocular (acuidade visual, sensibilidade ao contraste e à luminância e movimentos oculares); 2) com condições de visualização de uma imagem (iluminância da sala e luminância do monitor); e 3) fadiga ocular provocada pela observação diária consecutiva de imagens. Conclusões – A perceção visual pode ser influenciada por 3 categorias de erros observados: erros de pesquisa (lesões não são fixadas pela fóvea), erros de reconhecimento (lesões fixadas, mas não durante o tempo suficiente) e erros de decisão (lesões fixadas, mas não identificadas como suspeitas). Os estudos analisados sobre perceção visual, atenção visual e estratégia visual, bem como os estudos sobre condições de visualização não caracterizam a função visual dos observadores. Para uma avaliação correta da perceção visual em mamografia deverão ser efetuados estudos que correlacionem a função visual com a qualidade diagnóstica. ABSTRACT - Introduction – Diagnostic evaluation in mammography could be influenced by the radiologist performance that could be under diagnostic errors. Aims – To describe the importance of radiologist visual perception in mammographic diagnostic evaluation and to identify the main factors that contribute to diagnostic accuracy. Methods – In this systematic review 42 references were included based on inclusion criteria (PubMed and Science Direct). PRISMA method was used to select the references following 4 steps: identification, screening, eligibility and included references. Results – Visual perception in mammography diagnostic evaluation is related with: 1) visual parameters and ocular motility (visual acuity, contrast sensitivity and luminance and ocular movements); 2) image visualization environment (room iluminance and monitor luminance); and 3) eyestrain caused by image daily consecutive observation. Conclusions – Visual perception can be influenced by three errors categories: search errors (lesions are never looked at with high-resolution foveal vision), recognition errors (lesions are looked at, but not long enough to detect or recognize) and decision errors (lesions are looked at for long periods of time but are still missed). The reviewed studies concerning visual perception, visual attention, visual strategies and image visualization environment do not describe observer’s visual function. An accurate evaluation of visual perception in mammography must include visual function analysis.

Longe da vista, longe do coração: o design como “âncora” visual e elemento agregador da atividade museológica

To become an open to outer space, the "museum" acquired new forms and new expressions. The complexity of museological activity thus leads to new representations that alter the initial image of the museum as a building with objects. Their 'boundaries' are now less sharp, not only in relation to the spatial relationship, but also to its temporal dimension, creating an additional challenge which is the recognition of the museum itself. The design, while transdisciplinary activity, thereby assumes a key role in the communication of the museums in its visual representation and recognition of their action. The present study results from a survey conducted in 2010 to 364 Portuguese museums (from a universe of 849 museums), presenting an analysis to its base elements of visual expression of identity (name, logo, symbol, and color).

Real-Time Visual Ground-Truth System for Indoor Robotic Applications

The robotics community is concerned with the ability to infer and compare the results from researchers in areas such as vision perception and multi-robot cooperative behavior. To accomplish that task, this paper proposes a real-time indoor visual ground truth system capable of providing accuracy with at least more magnitude than the precision of the algorithm to be evaluated. A multi-camera architecture is proposed under the ROS (Robot Operating System) framework to estimate the 3D position of objects and the implementation and results were contextualized to the Robocup Middle Size League scenario.

Automatic visual detection of human behavior: a review from 2000 to 2014

Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

Development of a semi-automatic self learning pattern recognition system for the control of electronic boards

This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway - Mayo Institute of Technology and an industrial company, Tyco/Mallinckrodt Galway. The project aimed to develop a semi - automatic, self - learning pattern recognition system capable of detecting defects on the printed circuits boards such as component vacancy, component misalignment, component orientation, component error, and component weld. The research was conducted in three directions: image acquisition, image filtering/recognition and software development. Image acquisition studied the process of forming and digitizing images and some fundamental aspects regarding the human visual perception. The importance of choosing the right camera and illumination system for a certain type of problem has been highlighted. Probably the most important step towards image recognition is image filtering, The filters are used to correct and enhance images in order to prepare them for recognition. Convolution, histogram equalisation, filters based on Boolean mathematics, noise reduction, edge detection, geometrical filters, cross-correlation filters and image compression are some examples of the filters that have been studied and successfully implemented in the software application. The software application developed during the research is customized in order to meet the requirements of the industrial partner. The application is able to analyze pictures, perform the filtering, build libraries, process images and generate log files. It incorporates most of the filters studied and together with the illumination system and the camera it provides a fully integrated framework able to analyze defects on printed circuit boards.

Estimation of nonparametric probability density functions with applications to automatic speech recognition

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2007