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.

Expert opinion on best practice guidelines and competency framework for visual screening in children

PURPOSE: Screening programs to detect visual abnormalities in children vary among countries. The aim of this study is to describe experts' perception of best practice guidelines and competency framework for visual screening in children. METHODS: A qualitative focus group technique was applied during the Portuguese national orthoptic congress to obtain the perception of an expert panel of 5 orthoptists and 2 ophthalmologists with experience in visual screening for children (mean age 53.43 years, SD ± 9.40). The panel received in advance a script with the description of three tuning competencies dimensions (instrumental, systemic, and interpersonal) for visual screening. The session was recorded in video and audio. Qualitative data were analyzed using a categorical technique. RESULTS: According to experts' views, six tests (35.29%) have to be included in a visual screening: distance visual acuity test, cover test, bi-prism or 4/6(Δ) prism, fusion, ocular movements, and refraction. Screening should be performed according to the child age before and after 3 years of age (17.65%). The expert panel highlighted the influence of the professional experience in the application of a screening protocol (23.53%). They also showed concern about the false negatives control (23.53%). Instrumental competencies were the most cited (54.09%), followed by interpersonal (29.51%) and systemic (16.4%). CONCLUSIONS: Orthoptists should have professional experience before starting to apply a screening protocol. False negative results are a concern that has to be more thoroughly investigated. The proposed framework focuses on core competencies highlighted by the expert panel. Competencies programs could be important do develop better screening programs.

Rendimiento escolar e tipos de errores en la lectura en los niños con alteraciones de la función visual

Se desarrolló un estudio descriptivo con el objetivo de evaluar el rendimiento escolar así como tipos de errores en la lectura en niños con alteraciones de la función visual. En el estudio participaron 672 niños del Municipio de Lisboa (7.69±1.19 años): grupo de control (función visual normal=562) y grupo experimental (alteraciones da función visual=110). Se cuestionaron 34 profesores acerca del rendimiento escolar y lectura a través de un cuestionario validado. Para la evaluación en la lectura se empleó la prueba de lectura de 34 palabras sueltas. Los niños con la función visual alterada mostraron niveles más bajos de rendimiento escolar. Estaban en el nivel "negativo" del 10,9% de los niños con la función visual alterada y sólo del 5,3% de los niños con la función visual normal. Estos niños comenten más errores en la lectura (p<0,001) con un mayor número de no palabras (3,09±5,20) en comparación con los niños con la función visual normal (1,44±3,09). Comenten también más omisiones y adiciones de letras y confusiones de grafema, teniendo dificultades en el análisis global de la palabra. Se propone un modelo de orientación para los profesores.