Three-dimensional planar model estimation using multi-constraint knowledge based on k-means and RANSAC

Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC called Multiplane Model Estimation, which can estimate multiple plane models simultaneously from a noisy point cloud using the knowledge extracted from a scene (or an object) in order to reconstruct it accurately. This method comprises two steps: first, it clusters the data into planar faces that preserve some constraints defined by knowledge related to the object (e.g., the angles between faces); and second, the models of the planes are estimated based on these data using a novel multi-constraint RANSAC. We performed experiments in the clustering and RANSAC stages, which showed that the proposed method performed better than state-of-the-art methods.

Sistema de visão para aterragem automática de UAV

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Retinal image quality assessment through a visual similarity index

Retinal image quality is commonly analyzed through parameters inherited from instrumental optics. These parameters are defined for ‘good optics’ so they are hard to translate into visual quality metrics. Instead of using point or artificial functions, we propose a quality index that takes into account properties of natural images. These images usually show strong local correlations that help to interpret the image. Our aim is to derive an objective index that quantifies the quality of vision by taking into account the local structure of the scene, instead of focusing on a particular aberration. As we show, this index highly correlates with visual acuity and allows inter-comparison of natural images around the retina. The usefulness of the index is proven through the analysis of real eyes before and after undergoing corneal surgery, which usually are hard to analyze with standard metrics.

Face processing in humans is compatible with a simple shape-based model of vision

Understanding how the human visual system recognizes objects is one of the key challenges in neuroscience. Inspired by a large body of physiological evidence (Felleman and Van Essen, 1991; Hubel and Wiesel, 1962; Livingstone and Hubel, 1988; Tso et al., 2001; Zeki, 1993), a general class of recognition models has emerged which is based on a hierarchical organization of visual processing, with succeeding stages being sensitive to image features of increasing complexity (Hummel and Biederman, 1992; Riesenhuber and Poggio, 1999; Selfridge, 1959). However, these models appear to be incompatible with some well-known psychophysical results. Prominent among these are experiments investigating recognition impairments caused by vertical inversion of images, especially those of faces. It has been reported that faces that differ "featurally" are much easier to distinguish when inverted than those that differ "configurally" (Freire et al., 2000; Le Grand et al., 2001; Mondloch et al., 2002) ??finding that is difficult to reconcile with the aforementioned models. Here we show that after controlling for subjects' expectations, there is no difference between "featurally" and "configurally" transformed faces in terms of inversion effect. This result reinforces the plausibility of simple hierarchical models of object representation and recognition in cortex.

Advances in Model-Based Traffic Vision

Model based vision allows use of prior knowledge of the shape and appearance of specific objects to be used in the interpretation of a visual scene; it provides a powerful and natural way to enforce the view consistency constraint. A model based vision system has been developed within ESPRIT VIEWS: P2152 which is able to classify and track moving objects (cars and other vehicles) in complex, cluttered traffic scenes. The fundamental basis of the method has been previously reported. This paper presents recent developments which have extended the scope of the system to include (i) multiple cameras, (ii) variable camera geometry, and (iii) articulated objects. All three enhancements have easily been accommodated within the original model-based approach

A model of the mammalian retina and the visual cortex. Disorders of vision

A model of the mammalian retina and the behavior of the first layers in the visual cortex is reported. The building blocks are optically programmable logic cells. A model of the retina, similar to the one reported by Dowling (1987) is presented. From the model of the visual cortex obtained, some types of symmetries and asymmetries are possible to be detected

An approach to a model of the visual cortex: disorders of vision

One of the most challenging problems that must be solved by any theoretical model purporting to explain the competence of the human brain for relational tasks is the one related with the analysis and representation of the internal structure in an extended spatial layout of múltiple objects. In this way, some of the problems are related with specific aims as how can we extract and represent spatial relationships among objects, how can we represent the movement of a selected object and so on. The main objective of this paper is the study of some plausible brain structures that can provide answers in these problems. Moreover, in order to achieve a more concrete knowledge, our study will be focused on the response of the retinal layers for optical information processing and how this information can be processed in the first cortex layers. The model to be reported is just a first trial and some major additions are needed to complete the whole vision process.

Proinsulin slows retinal degeneration and vision loss in the P23H rat model of retinitis pigmentosa

Proinsulin has been characterized as a neuroprotective molecule. In this work we assess the therapeutic potential of proinsulin on photoreceptor degeneration, synaptic connectivity, and functional activity of the retina in the transgenic P23H rat, an animal model of autosomal dominant retinitis pigmentosa (RP). P23H homozygous rats received an intramuscular injection of an adeno-associated viral vector serotype 1 (AAV1) expressing human proinsulin (hPi+) or AAV1-null vector (hPi−) at P20. Levels of hPi in serum were determined by enzyme-linked immunosorbent assay (ELISA), and visual function was evaluated by electroretinographic (ERG) recording at P30, P60, P90, and P120. Preservation of retinal structure was assessed by immunohistochemistry at P120. Human proinsulin was detected in serum from rats injected with hPi+ at all times tested, with average hPi levels ranging from 1.1 nM (P30) to 1.4 nM (P120). ERG recordings showed an amelioration of vision loss in hPi+ animals. The scotopic b-waves were significantly higher in hPi+ animals than in control rats at P90 and P120. This attenuation of visual deterioration correlated with a delay in photoreceptor degeneration and the preservation of retinal cytoarchitecture. hPi+ animals had 48.7% more photoreceptors than control animals. Presynaptic and postsynaptic elements, as well as the synaptic contacts between photoreceptors and bipolar or horizontal cells, were preserved in hPi+ P23H rats. Furthermore, in hPi+ rat retinas the number of rod bipolar cell bodies was greater than in control rats. Our data demonstrate that hPi expression preserves cone and rod structure and function, together with their contacts with postsynaptic neurons, in the P23H rat. These data strongly support the further development of proinsulin-based therapy to counteract retinitis pigmentosa.

A profile of low vision services in England the Low Vision Service Model Evaluation (LOVSME) project

In the UK, low vision rehabilitation is delivered by a wide variety of providers with different strategies being used to integrate services from health, social care and the voluntary sector. In order to capture the current diversity of service provision the Low vision Service Model Evaluation (LOVSME) project aimed to profile selected low vision services using published standards for service delivery as a guide. Seven geographically and organizationally varied low-vision services across England were chosen for their diversity and all agreed to participate. A series of questionnaires and follow-up visits were undertaken to obtain a comprehensive description of each service, including the staff workloads and the cost of providing the service. In this paper the strengths of each model of delivery are discussed, and examples of good practice identified. As a result of the project, an Assessment Framework tool has been developed that aims to help other service providers evaluate different aspects of their own service to identify any gaps in existing service provision, and will act as a benchmark for future service development.

Surface roughness after excimer laser ablation using a PMMA model:profilometry and effects on vision

PURPOSE: To show that the limited quality of surfaces produced by one model of excimer laser systems can degrade visual performance with a polymethylmethacrylate (PMMA) model. METHODS: A range of lenses of different powers was ablated in PMMA sheets using five DOS-based Nidek EC-5000 laser systems (Nidek Technologies, Gamagori, Japan) from different clinics. Surface quality was objectively assessed using profilometry. Contrast sensitivity and visual acuity were measured through the lenses when their powers were neutralized with suitable spectacle trial lenses. RESULTS: Average surface roughness was found to increase with lens power, roughness values being higher for negative lenses than for positive lenses. Losses in visual contrast sensitivity and acuity measured in two subjects were found to follow a similar pattern. Findings are similar to those previously published with other excimer laser systems. CONCLUSIONS: Levels of surface roughness produced by some laser systems may be sufficient to degrade visual performance under some circumstances.

Contrast and lustre:a model that accounts for eleven different forms of contrast discrimination in binocular vision

Our goal here is a more complete understanding of how information about luminance contrast is encoded and used by the binocular visual system. In two-interval forced-choice experiments we assessed observers' ability to discriminate changes in contrast that could be an increase or decrease of contrast in one or both eyes, or an increase in one eye coupled with a decrease in the other (termed IncDec). The base or pedestal contrasts were either in-phase or out-of-phase in the two eyes. The opposed changes in the IncDec condition did not cancel each other out, implying that along with binocular summation, information is also available from mechanisms that do not sum the two eyes' inputs. These might be monocular mechanisms. With a binocular pedestal, monocular increments of contrast were much easier to see than monocular decrements. These findings suggest that there are separate binocular (B) and monocular (L,R) channels, but only the largest of the three responses, max(L,B,R), is available to perception and decision. Results from contrast discrimination and contrast matching tasks were described very accurately by this model. Stimuli, data, and model responses can all be visualized in a common binocular contrast space, allowing a more direct comparison between models and data. Some results with out-of-phase pedestals were not accounted for by the max model of contrast coding, but were well explained by an extended model in which gratings of opposite polarity create the sensation of lustre. Observers can discriminate changes in lustre alongside changes in contrast.

End-to-end Deep Metric Learning con Vision-Language Model per il Fashion Image Captioning

L'image captioning è un task di machine learning che consiste nella generazione di una didascalia, o caption, che descriva le caratteristiche di un'immagine data in input. Questo può essere applicato, ad esempio, per descrivere in dettaglio i prodotti in vendita su un sito di e-commerce, migliorando l'accessibilità del sito web e permettendo un acquisto più consapevole ai clienti con difficoltà visive. La generazione di descrizioni accurate per gli articoli di moda online è importante non solo per migliorare le esperienze di acquisto dei clienti, ma anche per aumentare le vendite online. Oltre alla necessità di presentare correttamente gli attributi degli articoli, infatti, descrivere i propri prodotti con il giusto linguaggio può contribuire a catturare l'attenzione dei clienti. In questa tesi, ci poniamo l'obiettivo di sviluppare un sistema in grado di generare una caption che descriva in modo dettagliato l'immagine di un prodotto dell'industria della moda dato in input, sia esso un capo di vestiario o un qualche tipo di accessorio. A questo proposito, negli ultimi anni molti studi hanno proposto soluzioni basate su reti convoluzionali e LSTM. In questo progetto proponiamo invece un'architettura encoder-decoder, che utilizza il modello Vision Transformer per la codifica delle immagini e GPT-2 per la generazione dei testi. Studiamo inoltre come tecniche di deep metric learning applicate in end-to-end durante l'addestramento influenzino le metriche e la qualità delle caption generate dal nostro modello.

Graph-based Vision-Language Model for Multi-Modal Retrieval of Fashion Products

Artificial Intelligence is reshaping the field of fashion industry in different ways. E-commerce retailers exploit their data through AI to enhance their search engines, make outfit suggestions and forecast the success of a specific fashion product. However, it is a challenging endeavour as the data they possess is huge, complex and multi-modal. The most common way to search for fashion products online is by matching keywords with phrases in the product's description which are often cluttered, inadequate and differ across collections and sellers. A customer may also browse an online store's taxonomy, although this is time-consuming and doesn't guarantee relevant items. With the advent of Deep Learning architectures, particularly Vision-Language models, ad-hoc solutions have been proposed to model both the product image and description to solve this problems. However, the suggested solutions do not exploit effectively the semantic or syntactic information of these modalities, and the unique qualities and relations of clothing items. In this work of thesis, a novel approach is proposed to address this issues, which aims to model and process images and text descriptions as graphs in order to exploit the relations inside and between each modality and employs specific techniques to extract syntactic and semantic information. The results obtained show promising performances on different tasks when compared to the present state-of-the-art deep learning architectures.

Systemic Model for Diagnosis of the Micro, Small and Medium Enterprises from Two Cities from the Countryside of the State of So Paulo in Brazil

This article presents a proposal of a systemic model composed for the micro and small companies (MSE) of the region of Ribeiro Preto and the agents which influenced their environment. The proposed model was based on Stafford Beer`s (Diagnosing the system for organizations. Chichester, Wiley, 1985) systemic methodologies VSM (Viable System Model) and on Werner Ulrich`s (1983) CSH (Critical Systems Heuristics). The VSM is a model for the diagnosis of the structure of an organization and of its flows of information through the application of the cybernetics concepts (Narvarte, In El Modelo del Sistema Viable-MSV: experiencias de su aplicacin en Chile. Proyecto Cerebro Colectivo del IAS, Santiago, 2001). On the other hand, CSH focus on the context of the social group applied to the systemic vision as a counterpoint to the organizational management view considered by the VSM. MSE of Ribeiro Preto and Sertozinho had been analyzed as organizations inserted in systems that relate and integrate with other systems concerning the public administration, entities of representation and promotion agencies. The research questions: which are the bonds of interaction among the subsystems in this process and who are the agents involved? The systemic approach not only diagnosed a social group, formed by MSE of Ribeiro Preto and Sertozinho, public authorities and support entities, but could also delineate answers that aimed the clarification of obscure questions generating financial assistance to the formularization of efficient actions for the development of this system.