Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

Grammatical priming of visual word recognition in fourth-grade children

Previous work examining context effects in children has been limited to semantic context. The current research examined the effects of grammatical priming of word-naming in fourth-grade children. In Experiment 1, children named both inflected and uninflected noun and verb target words faster when they were preceded by grammatically constraining primes than when they were preceded by neutral primes. Experiment 1 used a long stimulus onset asynchrony (SOA) interval of 750 msec. Experiment 2 replicated the grammatical priming effect at two SOA intervals (400 msec and 700 msec), suggesting that the grammatical priming effect does not reflect the operation of any gross strategic effects directly attributable to the long SOA interval employed in Experiment 1. Grammatical context appears to facilitate target word naming by constraining target word class. Further work is required to elucidate the loci of this effect.

Characterisation of chronic lateral epicondylalgia using the McGill pain questionnaire, visual analog scales, and quantitative sensory tests

Aims: To characterise chronic lateral epicondylalgia using the McGill Pain Questionnaire, Visual Analog Scales for pain and function, and Quantitative Sensory Tests; and to examine the relationship between these tests in a population with chronic lateral epicondylalgia. Method: Fifty-six patients (29 female, 27 male) diagnosed with unilateral lateral epicondylalgia of 18.7 months (mean) duration (range 1-300), with a mean age of 50.7 years (range 27-73) participated in this study. Each participant underwent assessment with the McGill Pain Questionnaire (MPQ), Visual Analog Scales (VAS) for pain and function. and Quantitative Sensory Tests (QST) including thermal and pressure pain thresholds, pain free grip strength, and neuromeningeal tissue testing via the upper limb tension test 2b (ULTT 2b). Results: Moderate correlation (r = .338-.514, p = .000-.013) was found between all indices of the MPQ and VAS for pain experienced in the previous 24 hours and week. Thermal pain threshold was found to be significantly higher in males. A significant poor to moderate correlation was found between the Pain Rating Index (PRI) in the sensory category of the MPQ and ULTT2b scores (r = .353, p = .038). There was no other significant correlation between MPQ and QST data. Pain free grip strength was poorly yet significantly correlated with duration of pathology (r = 318, p = .038). Conclusion: The findings of this study are in agreement with others (Melzack and Katz, 1994) regarding the multidimensional nature of pain, in a condition conventionally conceived as a musculoskeletal pain state. The findings also suggest that utilisation of only one pain measurement tool is unlikely to provide a thorough clinical picture of pain experienced with chronic lateral epicondylalgia.

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.

An Evaluation of Local Feature Combiners for Robot Visual Localization

In the last decade, local image features have been widely used in robot visual localization. To assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image to those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, we compare several candidate combiners with respect to their performance in the visual localization task. A deeper insight into the potential of the sum and product combiners is provided by testing two extensions of these algebraic rules: threshold and weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance. The voting method, whilst competitive to the algebraic rules in their standard form, is shown to be outperformed by both their modified versions.

Robot visual localization through local feature fusion: an evaluation of multiple classifiers combination approaches

In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.

Avaliação de vigas de madeira de Castanho tendo por base a classificação visual e ensaios não destrutivos

Dissertação de mestrado Internacional em Sustentabilidade do Ambiente Construído

Visual recognition systems in a car passenger compartment with the focus on facial driver identification

Magdeburg, Univ., Fak. für Informatik, Diss., 2014

Electrostimulation mapping of comprehension of auditory and visual words.

In order to spare functional areas during the removal of brain tumours, electrical stimulation mapping was used in 90 patients (77 in the left hemisphere and 13 in the right; 2754 cortical sites tested). Language functions were studied with a special focus on comprehension of auditory and visual words and the semantic system. In addition to naming, patients were asked to perform pointing tasks from auditory and visual stimuli (using sets of 4 different images controlled for familiarity), and also auditory object (sound recognition) and Token test tasks. Ninety-two auditory comprehension interference sites were observed. We found that the process of auditory comprehension involved a few, fine-grained, sub-centimetre cortical territories. Early stages of speech comprehension seem to relate to two posterior regions in the left superior temporal gyrus. Downstream lexical-semantic speech processing and sound analysis involved 2 pathways, along the anterior part of the left superior temporal gyrus, and posteriorly around the supramarginal and middle temporal gyri. Electrostimulation experimentally dissociated perceptual consciousness attached to speech comprehension. The initial word discrimination process can be considered as an "automatic" stage, the attention feedback not being impaired by stimulation as would be the case at the lexical-semantic stage. Multimodal organization of the superior temporal gyrus was also detected since some neurones could be involved in comprehension of visual material and naming. These findings demonstrate a fine graded, sub-centimetre, cortical representation of speech comprehension processing mainly in the left superior temporal gyrus and are in line with those described in dual stream models of language comprehension processing.

What happens in the first 200 ms of word reading : ERP studies on visual word recognition with top-down and bottom-up approaches /

In this thesis, three main questions were addressed using event-related potentials (ERPs): (1) the timing of lexical semantic access, (2) the influence of "top-down" processes on visual word processing, and (3) the influence of "bottom-up" factors on visual word processing. The timing of lexical semantic access was investigated in two studies using different designs. In Study 1,14 participants completed two tasks: a standard lexical decision (LD) task which required a word/nonword decision to each target stimulus, and a semantically primed version (LS) of it using the same category of words (e.g., animal) within each block following which participants made a category judgment. In Study 2, another 12 participants performed a standard semantic priming task, where target stimulus words (e.g., nurse) could be either semantically related or unrelated to their primes (e.g., doctor, tree) but the order of presentation was randomized. We found evidence in both ERP studies that lexical semantic access might occur early within the first 200 ms (at about 170 ms for Study 1 and at about 160 ms for Study 2). Our results were consistent with more recent ERP and eye-tracking studies and are in contrast with the traditional research focus on the N400 component. "Top-down" processes, such as a person's expectation and strategic decisions, were possible in Study 1 because of the blocked design, but they were not for Study 2 with a randomized design. Comparing results from two studies, we found that visual word processing could be affected by a person's expectation and the effect occurred early at a sensory/perceptual stage: a semantic task effect in the PI component at about 100 ms in the ERP was found in Study 1 , but not in Study 2. Furthermore, we found that such "top-down" influence on visual word processing might be mediated through separate mechanisms depending on whether the stimulus was a word or a nonword. "Bottom-up" factors involve inherent characteristics of particular words, such as bigram frequency (the total frequency of two-letter combinations of a word), word frequency (the frequency of the written form of a word), and neighborhood density (the number of words that can be generated by changing one letter of an original word or nonword). A bigram frequency effect was found when comparing the results from Studies 1 and 2, but it was examined more closely in Study 3. Fourteen participants performed a similar standard lexical decision task but the words and nonwords were selected systematically to provide a greater range in the aforementioned factors. As a result, a total of 18 word conditions were created with 18 nonword conditions matched on neighborhood density and neighborhood frequency. Using multiple regression analyses, we foimd that the PI amplitude was significantly related to bigram frequency for both words and nonwords, consistent with results from Studies 1 and 2. In addition, word frequency and neighborhood frequency were also able to influence the PI amplitude separately for words and for nonwords and there appeared to be a spatial dissociation between the two effects: for words, the word frequency effect in PI was found at the left electrode site; for nonwords, the neighborhood frequency effect in PI was fovind at the right elecfrode site. The implications of otir findings are discussed.

Ontology based Framework for News Extraction in Visual Media

Anticipating the increase in video information in future, archiving of news is an important activity in the visual media industry. When the volume of archives increases, it will be difficult for journalists to find the appropriate content using current search tools. This paper provides the details of the study we conducted about the news extraction systems used in different news channels in Kerala. Semantic web technologies can be used effectively since news archiving share many of the characteristics and problems of WWW. Since visual news archives of different media resources follow different metadata standards, interoperability between the resources is also an issue. World Wide Web Consortium has proposed a draft for an ontology framework for media resource which addresses the intercompatiblity issues. In this paper, the w3c proposed framework and its drawbacks is also discussed

The Use of Grouping in Visual Object Recognition.

The report describes a recognition system called GROPER, which performs grouping by using distance and relative orientation constraints that estimate the likelihood of different edges in an image coming from the same object. The thesis presents both a theoretical analysis of the grouping problem and a practical implementation of a grouping system. GROPER also uses an indexing module to allow it to make use of knowledge of different objects, any of which might appear in an image. We test GROPER by comparing it to a similar recognition system that does not use grouping.

Geometry and Photometry in 3D Visual Recognition

The report addresses the problem of visual recognition under two sources of variability: geometric and photometric. The geometric deals with the relation between 3D objects and their views under orthographic and perspective projection. The photometric deals with the relation between 3D matte objects and their images under changing illumination conditions. Taken together, an alignment-based method is presented for recognizing objects viewed from arbitrary viewing positions and illuminated by arbitrary settings of light sources.

A Detailed Look at Scale and Translation Invariance in a Hierarchical Neural Model of Visual Object Recognition

The HMAX model has recently been proposed by Riesenhuber & Poggio as a hierarchical model of position- and size-invariant object recognition in visual cortex. It has also turned out to model successfully a number of other properties of the ventral visual stream (the visual pathway thought to be crucial for object recognition in cortex), and particularly of (view-tuned) neurons in macaque inferotemporal cortex, the brain area at the top of the ventral stream. The original modeling study only used ``paperclip'' stimuli, as in the corresponding physiology experiment, and did not explore systematically how model units' invariance properties depended on model parameters. In this study, we aimed at a deeper understanding of the inner workings of HMAX and its performance for various parameter settings and ``natural'' stimulus classes. We examined HMAX responses for different stimulus sizes and positions systematically and found a dependence of model units' responses on stimulus position for which a quantitative description is offered. Interestingly, we find that scale invariance properties of hierarchical neural models are not independent of stimulus class, as opposed to translation invariance, even though both are affine transformations within the image plane.