Rotation Invariant Object Recognition from One Training Example

Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. Such a descriptor--based on a set of oriented Gaussian derivative filters-- is used in our recognition system. We report here an evaluation of several techniques for orientation estimation to achieve rotation invariance of the descriptor. We also describe feature selection based on a single training image. Virtual images are generated by rotating and rescaling the image and robust features are selected. The results confirm robust performance in cluttered scenes, in the presence of partial occlusions, and when the object is embedded in different backgrounds.

Pose Determination of a Grasped Object Using Limited Sensing

This report explores methods for determining the pose of a grasped object using only limited sensor information. The problem of pose determination is to find the position of an object relative to the hand. The information is useful when grasped objects are being manipulated. The problem is hard because of the large space of grasp configurations and the large amount of uncertainty inherent in dexterous hand control. By studying limited sensing approaches, the problem's inherent constraints can be better understood. This understanding helps to show how additional sensor data can be used to make recognition methods more effective and robust.

Uncertainty Propagation in Model-Based Recognition

Building robust recognition systems requires a careful understanding of the effects of error in sensed features. Error in these image features results in a region of uncertainty in the possible image location of each additional model feature. We present an accurate, analytic approximation for this uncertainty region when model poses are based on matching three image and model points, for both Gaussian and bounded error in the detection of image points, and for both scaled-orthographic and perspective projection models. This result applies to objects that are fully three- dimensional, where past results considered only two-dimensional objects. Further, we introduce a linear programming algorithm to compute the uncertainty region when poses are based on any number of initial matches. Finally, we use these results to extend, from two-dimensional to three- dimensional objects, robust implementations of alignmentt interpretation- tree search, and ransformation clustering.

Geometric Aspects of Visual Object Recognition

This thesis presents there important results in visual object recognition based on shape. (1) A new algorithm (RAST; Recognition by Adaptive Sudivisions of Tranformation space) is presented that has lower average-case complexity than any known recognition algorithm. (2) It is shown, both theoretically and empirically, that representing 3D objects as collections of 2D views (the "View-Based Approximation") is feasible and affects the reliability of 3D recognition systems no more than other commonly made approximations. (3) The problem of recognition in cluttered scenes is considered from a Bayesian perspective; the commonly-used "bounded-error errorsmeasure" is demonstrated to correspond to an independence assumption. It is shown that by modeling the statistical properties of real-scenes better, objects can be recognized more reliably.

Learning Three-Dimensional Shape Models for Sketch Recognition

Artifacts made by humans, such as items of furniture and houses, exhibit an enormous amount of variability in shape. In this paper, we concentrate on models of the shapes of objects that are made up of fixed collections of sub-parts whose dimensions and spatial arrangement exhibit variation. Our goals are: to learn these models from data and to use them for recognition. Our emphasis is on learning and recognition from three-dimensional data, to test the basic shape-modeling methodology. In this paper we also demonstrate how to use models learned in three dimensions for recognition of two-dimensional sketches of objects.

ROC parameters in item and context recognition. 'Par??metros ROC en el reconocimiento de items y contextos'

Resumen tomado de la publicaci??n. Resumen tambi??n en ingl??s

Use of decision trees in colour feature selection: application to object recognition in outdoor scenes

A new method for the automated selection of colour features is described. The algorithm consists of two stages of processing. In the first, a complete set of colour features is calculated for every object of interest in an image. In the second stage, each object is mapped into several n-dimensional feature spaces in order to select the feature set with the smallest variables able to discriminate the remaining objects. The evaluation of the discrimination power for each concrete subset of features is performed by means of decision trees composed of linear discrimination functions. This method can provide valuable help in outdoor scene analysis where no colour space has been demonstrated as being the most suitable. Experiment results recognizing objects in outdoor scenes are reported

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

A new approach to real time traffic sign recognition based on colour information

The automatic interpretation of conventional traffic signs is very complex and time consuming. The paper concerns an automatic warning system for driving assistance. It does not interpret the standard traffic signs on the roadside; the proposal is to incorporate into the existing signs another type of traffic sign whose information will be more easily interpreted by a processor. The type of information to be added is profuse and therefore the most important object is the robustness of the system. The basic proposal of this new philosophy is that the co-pilot system for automatic warning and driving assistance can interpret with greater ease the information contained in the new sign, whilst the human driver only has to interpret the "classic" sign. One of the codings that has been tested with good results and which seems to us easy to implement is that which has a rectangular shape and 4 vertical bars of different colours. The size of these signs is equivalent to the size of the conventional signs (approximately 0.4 m2). The colour information from the sign can be easily interpreted by the proposed processor and the interpretation is much easier and quicker than the information shown by the pictographs of the classic signs

Prevalencia y factores asociados de síntomas osteomusculares en miembro superior y cuello en los trabajadores de un call center

Objetivo: determinar la prevalencia en los últimos 6 meses de los síntomas de cuello y miembro superior además de sus factores asociados, en trabajadores de una entidad financiera call center en el periodo comprendido de abril a octubre del año 2009. Métodos: se realizó un análisis descriptivo trasversal, a través de la aplicación de un cuestionario de morbilidad sentida que abarcó aspectos demográficos, antecedentes personales y antecedentes laborales. La presencia de los síntomas se documentó en una tabla donde se confrontaron los síntomas osteomusculares y los segmentos afectados en los últimos 6 meses. Adicionalmente se les pidió a los sujetos identificar la postura más frecuente durante su trabajo mediante un diagrama. Resultados: los síntomas más prevalentes fueron dolor en la muñeca derecha (0,44; IC 95% 0,37 – 0,51), dolor en el cuello (0,43; IC95% 0,36 – 0,50), rigidez en el cuello (0,33; IC95% 0,26 – 0,40) y dolor en la mano derecha (0,36; IC95% 0,29 – 0,43). Se encontraron diferencias estadísticamente significativas en cuanto al género en la presencia de dolor en muñeca derecha (26,1% hombres contra 73,9% mujeres; p=0,005), dolor en mano derecha (25% hombres versus 75% mujeres; p=0,008), síntomas neurológicos en mano derecha (19,4% versus 80,6%; p=0,001) y dolor en hombro derecho (26,3% hombres versus 73,7% mujeres; p=0,048). También se evidencio una diferencia estadísticamente significativa en la prevalencia del síntoma dolor en muñeca derecha según el auto reporte de mayor exigencia en el desempeño (85,2% con la percepción de mayor exigencias, versus 14,8% en los sujetos que no; p=0,020). Además una diferencia estadísticamente significativa con mayor presencia de síntomas en muñecas y manos en sujetos con postura en dorsiflexión de de las mismas (muñeca derecha 72,8%, p=0,001; muñeca izquierda 43,5%, p=0,020; mano derecha 62%, p=0,003). Conclusión: después de realizar el estudio se encontró como principal síntoma el dolor, localizado en: la muñeca derecha, el cuello, la mano derecha y el hombro derecho, con diferencias mayores para el género femenino según la postura de las muñecas, lo que es compatible con las condiciones de trabajo y la respuesta fisiológica a estas condiciones.

Fomento de las certificaciones del talento humano y la biotecnología en las cadenas de las TIC

Teniendo en cuenta que las Tecnologías de la Información y las Comunicación (TIC) son incuestionables y están ahí, formando parte de la cultura tecnológica que nos rodea y con la que debemos convivir Incluimos en el concepto TIC, la biotecnología y la acreditación de procesos y certificación de talento humano en la prestación de servicios de salud teniendo en cuenta la importancia de los mismos en el desarrollo de nuestras regiones y a nivel nacional. La biotecnología y la acreditación en salud a través del tiempo han sido temas Cambiantes, siguiendo el ritmo de los continuos avances científicos y en un marco de globalización económica y cultural, contribuyen a la rápida obsolescencia de los conocimientos y a la emergencia de nuevos valores, provocando continuas transformaciones en nuestras estructuras económicas, sociales y culturales, e incidiendo en casi todos los aspectos de nuestra vida. La biotecnología comprende una amplia variedad de conocimientos y tecnologías que incluyen disciplinas básicas y aplicadas, logrando un impacto positivo en el progreso socioeconómico de los países que se han interesado en fortalecer el desarrollo y aplicación de la biotecnología en sus mercados. Por otro lado la acreditación de los diferentes servicios de salud y la certificación del talento humano en nuestro país se ha venido perfeccionando guiado por estándares competentes a nivel mundial lo que nos da una ventaja para la promoción, venta y reconocimiento de nuestros servicios de salud a nivel internacional.

Professional Recognition of Educator Practice Framework Handbook

UoS CPD Framework route