Rotation Invariant Real-time Face Detection and Recognition System

In this report, a face recognition system that is capable of detecting and recognizing frontal and rotated faces was developed. Two face recognition methods focusing on the aspect of pose invariance are presented and evaluated - the whole face approach and the component-based approach. The main challenge of this project is to develop a system that is able to identify faces under different viewing angles in realtime. The development of such a system will enhance the capability and robustness of current face recognition technology. The whole-face approach recognizes faces by classifying a single feature vector consisting of the gray values of the whole face image. The component-based approach first locates the facial components and extracts them. These components are normalized and combined into a single feature vector for classification. The Support Vector Machine (SVM) is used as the classifier for both approaches. Extensive tests with respect to the robustness against pose changes are performed on a database that includes faces rotated up to about 40 degrees in depth. The component-based approach clearly outperforms the whole-face approach on all tests. Although this approach isproven to be more reliable, it is still too slow for real-time applications. That is the reason why a real-time face recognition system using the whole-face approach is implemented to recognize people in color video sequences.

Priors Stabilizers and Basis Functions: From Regularization to Radial, Tensor and Additive Splines

We had previously shown that regularization principles lead to approximation schemes, as Radial Basis Functions, which are equivalent to networks with one layer of hidden units, called Regularization Networks. In this paper we show that regularization networks encompass a much broader range of approximation schemes, including many of the popular general additive models, Breiman's hinge functions and some forms of Projection Pursuit Regression. In the probabilistic interpretation of regularization, the different classes of basis functions correspond to different classes of prior probabilities on the approximating function spaces, and therefore to different types of smoothness assumptions. In the final part of the paper, we also show a relation between activation functions of the Gaussian and sigmoidal type.

Geometric and Algebraic Aspects of 3D Affine and Projective Structures from Perspective 2D Views

We investigate the differences --- conceptually and algorithmically --- between affine and projective frameworks for the tasks of visual recognition and reconstruction from perspective views. It is shown that an affine invariant exists between any view and a fixed view chosen as a reference view. This implies that for tasks for which a reference view can be chosen, such as in alignment schemes for visual recognition, projective invariants are not really necessary. We then use the affine invariant to derive new algebraic connections between perspective views. It is shown that three perspective views of an object are connected by certain algebraic functions of image coordinates alone (no structure or camera geometry needs to be involved).

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.

Matching Interest Points Using Projective Invariant Concentric Circles

We present a new method to perform reliable matching between different images. This method exploits a projective invariant property between concentric circles and the corresponding projected ellipses to find complete region correspondences centered on interest points. The method matches interest points allowing for a full perspective transformation and exploiting all the available luminance information in the regions. Experiments have been conducted on many different data sets to compare our approach to SIFT local descriptors. The results show the new method offers increased robustness to partial visibility, object rotation in depth, and viewpoint angle change.

Comparing methods for dimensionality reduction when data are density functions

Functional Data Analysis (FDA) deals with samples where a whole function is observed for each individual. A particular case of FDA is when the observed functions are density functions, that are also an example of infinite dimensional compositional data. In this work we compare several methods for dimensionality reduction for this particular type of data: functional principal components analysis (PCA) with or without a previous data transformation and multidimensional scaling (MDS) for diferent inter-densities distances, one of them taking into account the compositional nature of density functions. The difeerent methods are applied to both artificial and real data (households income distributions)

Modeling of hybrid systems by piecewise decomposition

Piecewise linear models systems arise as mathematical models of systems in many practical applications, often from linearization for nonlinear systems. There are two main approaches of dealing with these systems according to their continuous or discrete-time aspects. We propose an approach which is based on the state transformation, more particularly the partition of the phase portrait in different regions where each subregion is modeled as a two-dimensional linear time invariant system. Then the Takagi-Sugeno model, which is a combination of local model is calculated. The simulation results show that the Alpha partition is well-suited for dealing with such a system

Special Functions

Exam questions and solutions in LaTex

Special Functions pdf

Exam questions and solutions in PDF

Vector functions and curves

Exercises and solutions about vector functions and curves.

Análisis del Ejército Zapatista de Liberación Nacional como modelo de guerrilla estética, a la luz de la teoría de la resistencia planteada por Jacques Rancière

Justo ahora, cuando parece haberse agotado el entendimiento del zapatismo como movimiento revolucionario tradicional, esta monografía propone dar un doble salto mortal para destruir las barreras obsoletas de las teorías revolucionarias y aterrizar en lo que Rancière llama la Resistencia de los Sin Parte. El alarido bestial se transforma en palabra para sacudir las estructuras más íntimas del orden y actualizar la pésima partición de los lugares y las funciones comunes en la comunidad. Las partes mal contadas acceden a la palabra para reclamar una partición justa de lo común, e inscribir así las libertades como axiomas para el todo comunitario. Lo descolorido toma color, lo oculto es visto, lo incontado entra en el conteo de las partes, lo que no tiene rostro ni voz es ahora escuchado, las sombras adquieren cuerpos y los cuerpos adquieren vida. La resistencia por la incorporación cambió para siempre la política tradicional mexicana, al punto de que ésta ha dejado de llamarse como tal para quien escribió esta investigación. La palabra común, la imagen del líder Marcos, y los símbolos como el pasamontañas, hacen que la rebelión zapatista sea una rebelión desde y para los sin parte, una voz para incorporar a los sin voz: el rostro indefinido de una máscara que defiende con enjundia a los olvidados y los devuelve a la arena de los vistos. Chiapas habla, los fantasmas resucitan, las partes mal contadas reclaman una justa partición de lo visible en la comunidad. Marcos y los suyo se han salido con la suya.

Mnesic performance and executive functions in patients with multiple sclerosis (MS)

The Episodic Memory (EM) and the Executive Functions (EF) are cognitive areas that are affected in patients with diagnosis of Multiple Sclerosis (MS). Nowadays there exists scarce works destined to explore the infl uence of the EF on measures of mnesic performance in MS. For this reason, we analyze the effect of the EF on the performance in a set of memory measures. We worked with a clinical group (n=36) and with a control group (n=36) compared by age and educational level. The results show that the clinical group obtained significantly low average values in all the mnesic indexes (with exception of recognition) and in all the executive measures. All the executive indexes showed significant associations with some of the indexes of mnesic performance. These findings suggest that the problems in the episodic memory in EM patients could be analyzed as the manifestation of a global disorder that could be similar to the one that involves the EF. 

Rehabilitation of executive functions: Implications and strategies

Executive Functions (EF) concern a range of abilitiesincluding problem-solving, planning, initiation, selfmonitoring,conscious attention, cope with new situationsand the ability to modify plans if necessary. It’s ahigh cognitive function that is crucial for a person to getengaged and maintain daily activities whilst keeping agood quality of life. Problems in the EF were formerlyknown as Dysexecutive Syndrome (DS). There are manymodels concerning DS, although the literature on thesubject still remains unclear. Several works appoint theeffects brought by elderly life, as well as abuse of drugsand some psychopathologies. These factors are knownto increase the distress of the frontal circuits and thatcould be associated to executive deficits. The effects ofDS would compromise individuals in day-to-day routine,academic, social and labor fields. There is a growingbody of studies trying to determine the causes, implications,associations and the best way to take care of theseeffects. This work intends to review DS, focusing on themost important fields related to this area, such as psychopathologyassociations, cognitive reserve, assessmentand cognitive rehabilitation programs.

Executive functions in school-aged children: age and socioeconomic status effects

Lately, the study of prefrontal executive functions in grade scholars has noticeably increased. The aim of this study is to investigate the influence of age and socioeconomic status (sEs) on executive tasks performance and to analyze those socioeconomic variables that predict a better execution. A sample of 254 children aged between 7 and 12 years from the city of santa Fe, Argentina and belonging to different socioeconomic status were tested. A bat- tery of executive functions sensitive to prefrontal function was used to obtain the results. These in- dicate a significant influence of age and SES on executive functions. The cognitive patterns follow a different path according to the development and sEs effect. Besides, it is revealed a pattern of low cognitive functioning in low-sEs children in all executive functions. Finally, from the variables included in this study, it was found that only the educational level of the mother and the housing conditions are associated to the children’s executive function. The results are discussed in terms of the influence of the cerebral maturation and the envi- ronmental variables in the executive functioning.

Type 2 diabetes; elderly; cognitive deficit; cognitive flexibility; executive functions Resumen

Through meditation, people become aware of what happens in the body and mind, accepting the present experiences as they are and getting a better understanding of the true nature of things. Meditation practices and its inclusion as an intervention technique, have generated great interest in identifying the brain mechanisms through which these practices operate. Different studies suggest that the practice of meditation is associated with the use of different neural networks as well as changes in brain structure and function, represented in higher concentration of gray matter structures at the hippocampus, the right anterior insula, orbital frontal cortex (OFC) and greater involvement of the anterior cingulate cortex (ACC). These and other unrelated studies, shows the multiple implications of the regular practice of mindfulness in the structures and functions of the brain and its relation to certain observable and subjective states in people who practice it. Such evidence enabling the inclusion of mindfulness in psychological therapy where multiple applications have been developed to prove its effectiveness in treating affective and emotional problems, crisis management, social skills, verbal creativity, addiction and craving management, family and caregivers stress of dementia patients and others. However, neuropsychological rehabilitation has no formal proposals for intervention from these findings. The aim of this paper is to propose use of Mindfulness in neuropsychological rehabilitation process, taking the positions and theory of A.R. Luria.