Moving cast shadows detection methods for video surveillance applications

Moving cast shadows are a major concern in today’s performance from broad range of many vision-based surveillance applications because they highly difficult the object classification task. Several shadow detection methods have been reported in the literature during the last years. They are mainly divided into two domains. One usually works with static images, whereas the second one uses image sequences, namely video content. In spite of the fact that both cases can be analogously analyzed, there is a difference in the application field. The first case, shadow detection methods can be exploited in order to obtain additional geometric and semantic cues about shape and position of its casting object (’shape from shadows’) as well as the localization of the light source. While in the second one, the main purpose is usually change detection, scene matching or surveillance (usually in a background subtraction context). Shadows can in fact modify in a negative way the shape and color of the target object and therefore affect the performance of scene analysis and interpretation in many applications. This chapter wills mainly reviews shadow detection methods as well as their taxonomies related with the second case, thus aiming at those shadows which are associated with moving objects (moving shadows).Peer Reviewe

Control dinámico de sensor de cámara de captura como preproceso de reconocimiento ocular

Uno de los aspectos más difíciles de resolver cuando se realiza procesamiento de imágenes oculares en ambientes de diversas exposiciones lumínicas y con movimientos aleatorios de la cámara de captura, es el de homogenización de la imagen que se introduce al algoritmo de reconocimiento. El sistema propuesto utiliza dinámicamente los controles electrónicos de brillo y contraste del sensor de la cámara de captura (CCD, CMOS, etc.) lo que permite independizar cualquier sistema de reconocimiento ocular de las condiciones ambientales, simplificando de manera significativa el algoritmo de reconocimiento de imágenes por tener que trabajar con menos variables.One of the more difficult aspects of solving when an ocular image processing is made in atmospheres with several light exposition and aleatory movements of the capture camera, it’s the image standardization which is introduced in the recognition algorithm. The proposed system uses dynamically the electronic control parameters (brightness and contrast) of the capture camera sensor (CCD, CMOS, others) what allows to any ocular recognition system to be independent of the environmental conditions, simplifying the images recognition algorithm to work with less variables.IV Workshop de Computación Gráfica, Imágenes y Visualización (WCGIV)Red de Universidades con Carreras en Informática (RedUNCI

Control dinámico de sensor de cámara de captura como preproceso de reconocimiento ocular

Uno de los aspectos más difíciles de resolver cuando se realiza procesamiento de imágenes oculares en ambientes de diversas exposiciones lumínicas y con movimientos aleatorios de la cámara de captura, es el de homogenización de la imagen que se introduce al algoritmo de reconocimiento. El sistema propuesto utiliza dinámicamente los controles electrónicos de brillo y contraste del sensor de la cámara de captura (CCD, CMOS, etc.) lo que permite independizar cualquier sistema de reconocimiento ocular de las condiciones ambientales, simplificando de manera significativa el algoritmo de reconocimiento de imágenes por tener que trabajar con menos variables.One of the more difficult aspects of solving when an ocular image processing is made in atmospheres with several light exposition and aleatory movements of the capture camera, it’s the image standardization which is introduced in the recognition algorithm. The proposed system uses dynamically the electronic control parameters (brightness and contrast) of the capture camera sensor (CCD, CMOS, others) what allows to any ocular recognition system to be independent of the environmental conditions, simplifying the images recognition algorithm to work with less variables.IV Workshop de Computación Gráfica, Imágenes y Visualización (WCGIV)Red de Universidades con Carreras en Informática (RedUNCI

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Environment-Independent Moving Cast Shadow Suppression in Video Surveillance

Aquesta tesi està orientada a la detecció i l’eliminació d’ombres en moviment. Les ombres es poden definir com una part de l’escena que no està directament il·luminada, pel fet que la font d’il·luminació es troba obstruïda per un o diversos objectes. Sovint, les ombres en moviment que es troben en imatges o en seqüències de vídeo són causa d’errors en l’anàlisi del comportament humà. Això es deu a que les ombres poden causar una degradació dels resultats dels algorismes de processament d’imatges aplicats a: detecció d’objectes, segmentació, vídeo vigilància o en propòsits similars. En aquesta tesi primer s’analitzen exhaustivament els mètodes de detecció d’ombres en moviment, i després amb l’objectiu de compensar les seves limitacions es proposa un nou mètode de detecció i eliminació d’aquest tipus d’ombres. El mètode proposat no fa servir informació a priori de l’escena, ni tampoc es restringeix a un tipus d’escena en concret. A més, el mètode proposat pot detectar tant ombres acromàtiques com també les cromàtiques, fins i tot quan hi ha camuflatge (és a dir, quan hi ha una forta similitud de color entre el foreground i l’ombra). Aquest mètode explota una propietat de constància local de color aconseguida a causa de la supressió de la reflectància en les regions amb ombres. Per detectar les regions amb ombres en una escena, els valors de la imatge del background són dividits pels valors de la imatge actual, tots dos en l’espai de color RGB. Al llarg de la tesi es demostra com aquesta divisió serà utilitzada per detectar segments amb gradients baixos i constants, que al seu torn s’utilitzen per distingir entre ombres i foregrounds. Els resultats experimentals duts a terme sobre base de dades públiques mostren un rendiment superior dels mètodes proposats en aquesta Tesi, comparat amb els mètodes actuals més sofisticats de detecci ó i eliminació d’ombres. A més els resultats demostren que el mètode proposat és robust i precís a l’hora detectar diferents tipus d’ombres en diferents tipus de vídeos.This thesis is devoted to moving shadows detection and suppression. Shadows could be defined as the parts of the scene that are not directly illuminated by a light source due to obstructing object or objects. Often, moving shadows in images sequences are undesirable since they could cause degradation of the expected results during processing of images for object detection, segmentation, scene surveillance or similar purposes. In this thesis first moving shadow detection methods are exhaustively overviewed. Beside the mentioned methods from literature and to compensate their limitations a new moving shadow detection method is proposed. It requires no prior knowledge about the scene, nor is it restricted to assumptions about specific scene structures. Furthermore, the technique can detect both achromatic and chromatic shadows even in the presence of camouflage that occurs when foreground regions are very similar in color to shadowed regions. The method exploits local color constancy properties due to reflectance suppression over shadowed regions. To detect shadowed regions in a scene the values of the background image are divided by values of the current frame in the RGB color space. In the thesis how this luminance ratio can be used to identify segments with low gradient constancy is shown, which in turn distinguish shadows from foreground. Experimental results on a collection of publicly available datasets illustrate the superior performance of the proposed method compared with the most sophisticated state-of-the-art shadow detection algorithms. These results show that the proposed approach is robust and accurate over a broad range of shadow types and challenging video conditions

Moving cast shadow detection

Advisors: Mikhail G. Mozerov, Jordi Gonzàlez. Date and location of PhD thesis defense: 16 March 2012, Universitat Autònoma de BarcelonaMotion perception is an amazing innate ability of the creatures on the planet. This adroitness entails a functional advantage that enables species to compete better in the wild. The motion perception ability is usually employed at different levels, allowing from the simplest interaction with the 'physis' up to the most transcendental survival tasks. Among the five classical perception system , vision is the most widely used in the motion perception field. Millions years of evolution have led to a highly specialized visual system in humans, which is characterized by a tremendous accuracy as well as an extraordinary robustness. Although humans and an immense diversity of species can distinguish moving object with a seeming simplicity, it has proven to be a difficult and non trivial problem from a computational perspective. In the field of Computer Vision, the detection of moving objects is a challenging and fundamental research area. This can be referred to as the 'origin' of vast and numerous vision-based research sub-areas. Nevertheless, from the bottom to the top of this hierarchical analysis, the foundations still relies on when and where motion has occurred in an image. Pixels corresponding to moving objects in image sequences can be identified by measuring changes in their values. However, a pixel's value (representing a combination of color and brightness) could also vary due to other factors such as: variation in scene illumination, camera noise and nonlinear sensor responses among others. The challenge lies in detecting if the changes in pixels' value are caused by a genuine object movement or not. An additional challenging aspect in motion detection is represented by moving cast shadows. The paradox arises because a moving object and its cast shadow share similar motion patterns. However, a moving cast shadow is not a moving object. In fact, a shadow represents a photometric illumination effect caused by the relative position of the object with respect to the light sources. Shadow detection methods are mainly divided in two domains depending on the application field. One normally consists of static images where shadows are casted by static objects, whereas the second one is referred to image sequences where shadows are casted by moving objects. For the first case, shadows can provide additional geometric and semantic cues about shape and position of its casting object as well as the localization of the light source. Although the previous information can be extracted from static images as well as video sequences, the main focus in the second area is usually change detection, scene matching or surveillance. In this context, a shadow can severely affect with the analysis and interpretation of the scene. The work done in the thesis is focused on the second case, thus it addresses the problem of detection and removal of moving cast shadows in video sequences in order to enhance the detection of moving object

Un nuevo estilo de gestión y sus implicancias en los Centros Educativos Franciscanos

Los Centros Educativos Franciscanos pertenecen a la Orden de Frailes Menores y en la actualidad hay 14 en la Argentina. Tradicionalmente, dichos centros eran presididos por un fraile. En el año 2005, la orden decidió realizar una profunda reforma, siendo lo más conflictivo y tal vez emblemático, sacar a los religiosos que eran representantes legales y unificar este rol con un nuevo rol llamado “director general”, cargo que sería ocupado por laicos. El objetivo de este documento es describir las implicancias que tuvieron la implementación del nuevo tipo de Gestión y Organización en dichos Centros Educativos. El documento incluye un diseño exploratorio secuencial, el cual tiene una fase inicial de recolección de datos cualitativos seguida de otra donde se obtiene y se analiza la información cuantitativa. Finalmente, se busca derivar conclusiones a partir del entrecruzamiento de la información obtenida en la etapa anterior, según los lineamientos particulares de algunos autores especializados en comportamiento organizacional

Un nuevo estilo de gestión y sus implicancias en los Centros Educativos Franciscanos

Los Centros Educativos Franciscanos pertenecen a la Orden de Frailes Menores y en la actualidad hay 14 en la Argentina. Tradicionalmente, dichos centros eran presididos por un fraile. En el año 2005, la orden decidió realizar una profunda reforma, siendo lo más conflictivo y tal vez emblemático, sacar a los religiosos que eran representantes legales y unificar este rol con un nuevo rol llamado “director general”, cargo que sería ocupado por laicos. El objetivo de este documento es describir las implicancias que tuvieron la implementación del nuevo tipo de Gestión y Organización en dichos Centros Educativos. El documento incluye un diseño exploratorio secuencial, el cual tiene una fase inicial de recolección de datos cualitativos seguida de otra donde se obtiene y se analiza la información cuantitativa. Finalmente, se busca derivar conclusiones a partir del entrecruzamiento de la información obtenida en la etapa anterior, según los lineamientos particulares de algunos autores especializados en comportamiento organizacional

Exploiting multiple cues in motion segmentation based on background subtraction

This paper presents a novel algorithm for mobile-object segmentation from static background scenes, which is both robust and accurate under most of the common problems found in motion segmentation. In our first contribution, a case analysis of motion segmentation errors is presented taking into account the inaccuracies associated with different cues, namely colour, edge and intensity. Our second contribution is an hybrid architecture which copes with the main issues observed in the case analysis by fusing the knowledge from the aforementioned three cues and a temporal difference algorithm. On one hand, we enhance the colour and edge models to solve not only global and local illumination changes (i.e. shadows and highlights) but also the camouflage in intensity. In addition, local information is also exploited to solve the camouflage in chroma. On the other hand, the intensity cue is applied when colour and edge cues are not available because their values are beyond the dynamic range. Additionally, temporal difference scheme is included to segment motion where those three cues cannot be reliably computed, for example in those background regions not visible during the training period. Lastly, our approach is extended for handling ghost detection. The proposed method obtains very accurate and robust motion segmentation results in multiple indoor and outdoor scenarios, while outperforming the most-referred state-of-art approaches. © 2012 Elsevier B.V.This work has beensupported by the Spanish Research Programs Consolider-Ingenio 2010: MIPRCV (CSD200700018); Avanza I+D ViCoMo (TSI-020400-2009-133); along with the Spanish projects TIN2009-14501-C02-01,TIN2009-14501-C02-02, and DIP2010-17112.Peer Reviewe