From detection of complex motion to descriptions of moving surfaces in human vision

A preliminary study by Freeman et al (1996b) has suggested that when complex patterns of motion elicit impressions of 2-dimensionality, odd-item-out detection improves given targets can be differentiated on the basis of surface properties. Their results can be accounted for, it if is supposed that observers are permitted efficient access to 3-D surface descriptions but access to 2-D motion descriptions is restricted. To test the hypothesis, a standard search technique was employed, in which targets could be discussed on the basis of slant sign. In one experiment, slant impressions were induced through the summing of deformation and translation components. In a second theory were induced through the summing of shear and translation components. Neither showed any evidence of efficient access. A third experiment explored the possibility that access to these representations may have been hindered by a lack of grouping between the stimuli. Attempts to improve grouping failed to produce convincing evidence in support of life. An alternative explanation is that complex patterns of motion are simply not processed simultaneously. Psychophysical and physiological studies have, however, suggested that multiple mechanisms selective for complex motion do exist. Using a subthreshold summation technique I found evidence supporting the notion that complex motions are processed in parallel. Furthermore, in a spatial summation experiment, coherence thresholds were measured for displays containing different numbers of complex motion patches. Consistent with the idea that complex motion processing proceeds in parallel, increases in the number of motion patches were seen to decrease thresholds, both for expansion and rotation. Moreover, the rates of decrease were higher than those typically expected from probability summation, thus implying mechanisms are available, which can pool signals from spatially distinct complex motion flows.

Psychophysical investigations of human peripheral vision

This thesis investigates various aspects of peripheral vision, which is known not to be as acute as vision at the point of fixation. Differences between foveal and peripheral vision are generally thought to be of a quantitative rather than a qualitative nature. However, the rate of decline in sensitivity between foveal and peripheral vision is known to be task dependent and the mechanisms underlying the differences are not yet well understood. Several experiments described here have employed a psychophysical technique referred to as 'spatial scaling'. Thresholds are determined at several eccentricities for ranges of stimuli which are magnified versions of one another. Using this methodology a parameter called the E2 value is determined, which defines the eccentricity at which stimulus size must double in order to maintain performance equivalent to that at the fovea. Experiments of this type have evaluated the eccentricity dependencies of detection tasks (kinetic and static presentation of a differential light stimulus), resolution tasks (bar orientation discrimination in the presence of flanking stimuli, word recognition and reading performance), and relative localisation tasks (curvature detection and discrimination). Most tasks could be made equal across the visual field by appropriate magnification. E2 values are found to vary widely dependent on the task, and possible reasons for such variations are discussed. The dependence of positional acuity thresholds on stimulus eccentricity, separation and spatial scale parameters is also examined. The relevance of each factor in producing 'Weber's law' for position can be determined from the results.

Grid-texture mechanisms in human vision:contrast detection of regular sparse micro-patterns requires specialist templates

Previous work has shown that human vision performs spatial integration of luminance contrast energy, where signals are squared and summed (with internal noise) over area at detection threshold. We tested that model here in an experiment using arrays of micro-pattern textures that varied in overall stimulus area and sparseness of their target elements, where the contrast of each element was normalised for sensitivity across the visual field. We found a power-law improvement in performance with stimulus area, and a decrease in sensitivity with sparseness. While the contrast integrator model performed well when target elements constituted 50–100% of the target area (replicating previous results), observers outperformed the model when texture elements were sparser than this. This result required the inclusion of further templates in our model, selective for grids of various regular texture densities. By assuming a MAX operation across these noisy mechanisms the model also accounted for the increase in the slope of the psychometric function that occurred as texture density decreased. Thus, for the first time, mechanisms that are selective for texture density have been revealed at contrast detection threshold. We suggest that these mechanisms have a role to play in the perception of visual textures.

Identification of characteristic volatile organic compounds released during the decomposition process of human remains and analogues

The manner in which remains decompose has been and is currently being researched around the world, yet little is still known about the generated scent of death. In fact, it was not until the Casey Anthony trial that research on the odor released from decomposing remains, and the compounds that it is comprised of, was brought to light. The Anthony trial marked the first admission of human decomposition odor as forensic evidence into the court of law; however, it was not "ready for prime time" as the scientific research on the scent of death is still in its infancy. This research employed the use of solid-phase microextraction (SPME) with gas chromatography-mass spectrometry (GC-MS) to identify the volatile organic compounds (VOCs) released from decomposing remains and to assess the impact that different environmental conditions had on the scent of death. Using human cadaver analogues, it was discovered that the environment in which the remains were exposed to dramatically affected the odors released by either modifying the compounds that it was comprised of or by enhancing/hindering the amount that was liberated. In addition, the VOCs released during the different stages of the decomposition process for both human remains and analogues were evaluated. Statistical analysis showed correlations between the stage of decay and the VOCs generated, such that each phase of decomposition was distinguishable based upon the type and abundance of compounds that comprised the odor. This study has provided new insight into the scent of death and the factors that can dramatically affect it, specifically, frozen, aquatic, and soil environments. Moreover, the results revealed that different stages of decomposition were distinguishable based upon the type and total mass of each compound present. Thus, based upon these findings, it is suggested that the training aids that are employed for human remains detection (HRD) canines should 1) be characteristic of remains that have undergone decomposition in different environmental settings, and 2) represent each stage of decay, to ensure that the HRD canines have been trained to the various odors that they are likely to encounter in an operational situation.

Adaptive unsupervised learning of human actions

Automatic detection of suspicious activities in CCTV camera feeds is crucial to the success of video surveillance systems. Such a capability can help transform the dumb CCTV cameras into smart surveillance tools for fighting crime and terror. Learning and classification of basic human actions is a precursor to detecting suspicious activities. Most of the current approaches rely on a non-realistic assumption that a complete dataset of normal human actions is available. This paper presents a different approach to deal with the problem of understanding human actions in video when no prior information is available. This is achieved by working with an incomplete dataset of basic actions which are continuously updated. Initially, all video segments are represented by Bags-Of-Words (BOW) method using only Term Frequency-Inverse Document Frequency (TF-IDF) features. Then, a data-stream clustering algorithm is applied for updating the system's knowledge from the incoming video feeds. Finally, all the actions are classified into different sets. Experiments and comparisons are conducted on the well known Weizmann and KTH datasets to show the efficacy of the proposed approach.

Automatic tracking, super-resolution and recognition of human faces from surveillance video

Identifying an individual from surveillance video is a difficult, time consuming and labour intensive process. The proposed system aims to streamline this process by filtering out unwanted scenes and enhancing an individual's face through super-resolution. An automatic face recognition system is then used to identify the subject or present the human operator with likely matches from a database. A person tracker is used to speed up the subject detection and super-resolution process by tracking moving subjects and cropping a region of interest around the subject's face to reduce the number and size of the image frames to be super-resolved respectively. In this paper, experiments have been conducted to demonstrate how the optical flow super-resolution method used improves surveillance imagery for visual inspection as well as automatic face recognition on an Eigenface and Elastic Bunch Graph Matching system. The optical flow based method has also been benchmarked against the ``hallucination'' algorithm, interpolation methods and the original low-resolution images. Results show that both super-resolution algorithms improved recognition rates significantly. Although the hallucination method resulted in slightly higher recognition rates, the optical flow method produced less artifacts and more visually correct images suitable for human consumption.

Corneal confocal microscopy : a novel noninvasive test to diagnose and stratify the severity of human diabetic neuropathy

OBJECTIVE: The accurate quantification of human diabetic neuropathy is important to define at-risk patients, anticipate deterioration, and assess new therapies. ---------- RESEARCH DESIGN AND METHODS: A total of 101 diabetic patients and 17 age-matched control subjects underwent neurological evaluation, neurophysiology tests, quantitative sensory testing, and evaluation of corneal sensation and corneal nerve morphology using corneal confocal microscopy (CCM). ---------- RESULTS: Corneal sensation decreased significantly (P = 0.0001) with increasing neuropathic severity and correlated with the neuropathy disability score (NDS) (r = 0.441, P < 0.0001). Corneal nerve fiber density (NFD) (P < 0.0001), nerve fiber length (NFL), (P < 0.0001), and nerve branch density (NBD) (P < 0.0001) decreased significantly with increasing neuropathic severity and correlated with NDS (NFD r = −0.475, P < 0.0001; NBD r = −0.511, P < 0.0001; and NFL r = −0.581, P < 0.0001). NBD and NFL demonstrated a significant and progressive reduction with worsening heat pain thresholds (P = 0.01). Receiver operating characteristic curve analysis for the diagnosis of neuropathy (NDS >3) defined an NFD of <27.8/mm2 with a sensitivity of 0.82 (95% CI 0.68–0.92) and specificity of 0.52 (0.40–0.64) and for detecting patients at risk of foot ulceration (NDS >6) defined a NFD cutoff of <20.8/mm2 with a sensitivity of 0.71 (0.42–0.92) and specificity of 0.64 (0.54–0.74). ---------- CONCLUSIONS: CCM is a noninvasive clinical technique that may be used to detect early nerve damage and stratify diabetic patients with increasing neuropathic severity. Established diabetic neuropathy leads to pain and foot ulceration. Detecting neuropathy early may allow intervention with treatments to slow or reverse this condition (1). Recent studies suggested that small unmyelinated C-fibers are damaged early in diabetic neuropathy (2–4) but can only be detected using invasive procedures such as sural nerve biopsy (4,5) or skin-punch biopsy (6–8). Our studies have shown that corneal confocal microscopy (CCM) can identify early small nerve fiber damage and accurately quantify the severity of diabetic neuropathy (9–11). We have also shown that CCM relates to intraepidermal nerve fiber loss (12) and a reduction in corneal sensitivity (13) and detects early nerve fiber regeneration after pancreas transplantation (14). Recently we have also shown that CCM detects nerve fiber damage in patients with Fabry disease (15) and idiopathic small fiber neuropathy (16) when results of electrophysiology tests and quantitative sensory testing (QST) are normal. In this study we assessed corneal sensitivity and corneal nerve morphology using CCM in diabetic patients stratified for the severity of diabetic neuropathy using neurological evaluation, electrophysiology tests, and QST. This enabled us to compare CCM and corneal esthesiometry with established tests of diabetic neuropathy and define their sensitivity and specificity to detect diabetic patients with early neuropathy and those at risk of foot ulceration.

Monocular myopic defocus and daily changes in axial length and choroidal thickness of human eyes

Recent research indicates that brief periods (60 minutes) of monocular defocus lead to small but significant changes in human axial length. However, the effects of longer periods of defocus on the axial length of human eyes are unknown. We examined the influence of a 12 hour period of monocular myopic defocus on the natural daily variations occurring in axial length and choroidal thickness of young adult emmetropes. A series of axial length and choroidal thickness measurements (collected at ~3 hourly intervals, with the first measurement at ~9 am and the final measurement at ~9 pm) were obtained for 13 emmetropic young adults over three consecutive days. The natural daily rhythms (Day 1, baseline day, no defocus), the daily rhythms with monocular myopic defocus (Day 2, defocus day, +1.50 DS spectacle lens over the right eye), and the recovery from any defocus induced changes (Day 3, recovery day, no defocus) were all examined. Significant variations over the course of the day were observed in both axial length and choroidal thickness on each of the three measurement days (p<0.0001). The magnitude and timing of the daily variations in axial length and choroidal thickness were significantly altered with the monocular myopic defocus on day 2 (p<0.0001). Following the introduction of monocular myopic defocus, the daily peak in axial length occurred approximately 6 hours later, and the peak in choroidal thickness approximately 8.5 hours earlier in the day compared to days 1 and 3 (with no defocus). The mean amplitude (peak to trough) of change in axial length (0.030 ± 0.012 on day 1, 0.020 ± 0.010 on day 2 and 0.033 ± 0.012 mm on day 3) and choroidal thickness (0.030 ± 0.007 on day 1, 0.022 ± 0.006 on day 2 and 0.027 ± 0.009 mm on day 3) were also significantly different between the three days (both p<0.05). The introduction of monocular myopic defocus disrupts the daily variations in axial length and choroidal thickness of human eyes (in terms of both amplitude and timing) that return to normal the following day after removal of the defocus.

Towards a capabilities database to inform inclusive design : Experimental investigation of effective survey-based predictors of human-product interaction

A key issue in the field of inclusive design is the ability to provide designers with an understanding of people's range of capabilities. Since it is not feasible to assess product interactions with a large sample, this paper assesses a range of proxy measures of design-relevant capabilities. It describes a study that was conducted to identify which measures provide the best prediction of people's abilities to use a range of products. A detailed investigation with 100 respondents aged 50-80 years was undertaken to examine how they manage typical household products. Predictor variables included self-report and performance measures across a variety of capabilities (vision, hearing, dexterity and cognitive function), component activities used in product interactions (e.g. using a remote control, touch screen) and psychological characteristics (e.g. self-efficacy, confidence with using electronic devices). Results showed, as expected, a higher prevalence of visual, hearing, dexterity, cognitive and product interaction difficulties in the 65-80 age group. Regression analyses showed that, in addition to age, performance measures of vision (acuity, contrast sensitivity) and hearing (hearing threshold) and self-report and performance measures of component activities are strong predictors of successful product interactions. These findings will guide the choice of measures to be used in a subsequent national survey of design-relevant capabilities, which will lead to the creation of a capability database. This will be converted into a tool for designers to understand the implications of their design decisions, so that they can design products in a more inclusive way.

Diurnal variations in ocular aberrations of human eyes

Purpose: To investigate the diurnal variations in ocular wavefront aberrations over two consecutive days in young adult subjects. Materials and methods: Measurements of both lower-order (sphero-cylindrical refractive powers) and higher-order (3rd and 4th order aberration terms) ocular aberrations were collected for 30 young adult subjects at ten different times over two consecutive days using a Hartmann-Shack aberrometer. Fifteen subjects were myopic and 15 were emmetropic. Five sets of measurements were collected each day at approximately 3 hourly intervals, with the first measurement taken at ~9 am and the final measurement at ~9 pm. Results: Spherical equivalent refraction (p = 0.029) and spherical aberration (p = 0.043) were both found to undergo significant diurnal variation over the two measurement days. The spherical equivalent was typically found to be at a maximum (i.e. most hyperopic) at the morning measurement, with a small myopic shift of 0.37 ± 0.15 D observed over the course of the day. The mean spherical aberration of all subjects (0.038 ± 0.048 μm) was found to be positive during the day and gradually became more negative into the evening, with a mean amplitude of change of 0.036 ± 0.02 μm. None of the other considered sphero-cylindrical refractive power components or higher-order aberrations exhibited significant diurnal variation over the two days of the experiment (p>0.05). Except for the lower-order astigmatism at 90/180 deg (p = 0.040), there were no significant differences between myopes and emmetropes in the magnitude and timing of the observed diurnal variations (p>0.05). Conclusions: Significant diurnal variations in spherical equivalent and spherical aberration were consistently observed over two consecutive days of measurement. Research and clinical applications requiring precise refractive error and wavefront measurements should take these diurnal changes into account when interpreting wavefront data.

Automatic classification of human epithelial type 2 cell indirect immunofluorescence images using cell pyramid matching

This paper describes a novel system for automatic classification of images obtained from Anti-Nuclear Antibody (ANA) pathology tests on Human Epithelial type 2 (HEp-2) cells using the Indirect Immunofluorescence (IIF) protocol. The IIF protocol on HEp-2 cells has been the hallmark method to identify the presence of ANAs, due to its high sensitivity and the large range of antigens that can be detected. However, it suffers from numerous shortcomings, such as being subjective as well as time and labour intensive. Computer Aided Diagnostic (CAD) systems have been developed to address these problems, which automatically classify a HEp-2 cell image into one of its known patterns (eg. speckled, homogeneous). Most of the existing CAD systems use handpicked features to represent a HEp-2 cell image, which may only work in limited scenarios. We propose a novel automatic cell image classification method termed Cell Pyramid Matching (CPM), which is comprised of regional histograms of visual words coupled with the Multiple Kernel Learning framework. We present a study of several variations of generating histograms and show the efficacy of the system on two publicly available datasets: the ICPR HEp-2 cell classification contest dataset and the SNPHEp-2 dataset.

Selectivity of human retinotopic visual cortex to S-cone-opponent, L/M-cone-opponent and achromatic stimulation

Our aim was to make a quantitative comparison of the response of the different visual cortical areas to selective stimulation of the two different cone-opponent pathways [long- and medium-wavelength (L/M)- and short-wavelength (S)-cone-opponent] and the achromatic pathway under equivalent conditions. The appropriate stimulus-contrast metric for the comparison of colour and achromatic sensitivity is unknown, however, and so a secondary aim was to investigate whether equivalent fMRI responses of each cortical area are predicted by stimulus contrast matched in multiples of detection threshold that approximately equates for visibility, or direct (cone) contrast matches in which psychophysical sensitivity is uncorrected. We found that the fMRI response across the two colour and achromatic pathways is not well predicted by threshold-scaled stimuli (perceptual visibility) but is better predicted by cone contrast, particularly for area V1. Our results show that the early visual areas (V1, V2, V3, VP and hV4) all have robust responses to colour. No area showed an overall colour preference, however, until anterior to V4 where we found a ventral occipital region that has a significant preference for chromatic stimuli, indicating a functional distinction from earlier areas. We found that all of these areas have a surprisingly strong response to S-cone stimuli, at least as great as the L/M response, suggesting a relative enhancement of the S-cone cortical signal. We also identified two areas (V3A and hMT+) with a significant preference for achromatic over chromatic stimuli, indicating a functional grouping into a dorsal pathway with a strong magnocellular input.

A Survey of autonomous vision-based See and Avoid for Unmanned Aircraft Systems

This paper provides a comprehensive review of the vision-based See and Avoid problem for unmanned aircraft. The unique problem environment and associated constraints are detailed, followed by an in-depth analysis of visual sensing limitations. In light of such detection and estimation constraints, relevant human, aircraft and robot collision avoidance concepts are then compared from a decision and control perspective. Remarks on system evaluation and certification are also included to provide a holistic review approach. The intention of this work is to clarify common misconceptions, realistically bound feasible design expectations and offer new research directions. It is hoped that this paper will help us to unify design efforts across the aerospace and robotics communities.

Feature integration in human vision

The earliest stages of human cortical visual processing can be conceived as extraction of local stimulus features. However, more complex visual functions, such as object recognition, require integration of multiple features. Recently, neural processes underlying feature integration in the visual system have been under intensive study. A specialized mid-level stage preceding the object recognition stage has been proposed to account for the processing of contours, surfaces and shapes as well as configuration. This thesis consists of four experimental, psychophysical studies on human visual feature integration. In two studies, classification image a recently developed psychophysical reverse correlation method was used. In this method visual noise is added to near-threshold stimuli. By investigating the relationship between random features in the noise and observer s perceptual decision in each trial, it is possible to estimate what features of the stimuli are critical for the task. The method allows visualizing the critical features that are used in a psychophysical task directly as a spatial correlation map, yielding an effective "behavioral receptive field". Visual context is known to modulate the perception of stimulus features. Some of these interactions are quite complex, and it is not known whether they reflect early or late stages of perceptual processing. The first study investigated the mechanisms of collinear facilitation, where nearby collinear Gabor flankers increase the detectability of a central Gabor. The behavioral receptive field of the mechanism mediating the detection of the central Gabor stimulus was measured by the classification image method. The results show that collinear flankers increase the extent of the behavioral receptive field for the central Gabor, in the direction of the flankers. The increased sensitivity at the ends of the receptive field suggests a low-level explanation for the facilitation. The second study investigated how visual features are integrated into percepts of surface brightness. A novel variant of the classification image method with brightness matching task was used. Many theories assume that perceived brightness is based on the analysis of luminance border features. Here, for the first time this assumption was directly tested. The classification images show that the perceived brightness of both an illusory Craik-O Brien-Cornsweet stimulus and a real uniform step stimulus depends solely on the border. Moreover, the spatial tuning of the features remains almost constant when the stimulus size is changed, suggesting that brightness perception is based on the output of a single spatial frequency channel. The third and fourth studies investigated global form integration in random-dot Glass patterns. In these patterns, a global form can be immediately perceived, if even a small proportion of random dots are paired to dipoles according to a geometrical rule. In the third study the discrimination of orientation structure in highly coherent concentric and Cartesian (straight) Glass patterns was measured. The results showed that the global form was more efficiently discriminated in concentric patterns. The fourth study investigated how form detectability depends on the global regularity of the Glass pattern. The local structure was either Cartesian or curved. It was shown that randomizing the local orientation deteriorated the performance only with the curved pattern. The results give support for the idea that curved and Cartesian patterns are processed in at least partially separate neural systems.