953 resultados para Pushbroom camera
Resumo:
Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of nontextured objets or objets for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance
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Getting images from a Digital Camera is pretty straight forward. However this is the easy part, its getting the right image and making sure your digital file is good enough for your output. Set you camera or mobile phone to the highest settings, this will give you more options when you come to manipulate or edit the file Remember to make copies of files for editing so you can always return to your original image if you need too
Resumo:
Seminario realizado por cuatro profesoras de distintos centros educativos de Vizcaya para la elaboración de cinco 'projects', cada uno con ejercicios para diferentes niveles, que tienen como objetivo inmediato la práctica de estructuras del lenguaje en un marco comunicativo y como objetivo global la realización de una filmación sobre el tema básico del project. Los temas tratados son: el uso de la cámara de vídeo, las noticias, los anuncios (publicidad), video clips, cuentos y narraciones. Los resultados se valoran como muy positivos debido a la motivación de filmar el producto final.
Resumo:
The paper reports an interactive tool for calibrating a camera, suitable for use in outdoor scenes. The motivation for the tool was the need to obtain an approximate calibration for images taken with no explicit calibration data. Such images are frequently presented to research laboratories, especially in surveillance applications, with a request to demonstrate algorithms. The method decomposes the calibration parameters into intuitively simple components, and relies on the operator interactively adjusting the parameter settings to achieve a visually acceptable agreement between a rectilinear calibration model and his own perception of the scene. Using the tool, we have been able to calibrate images of unknown scenes, taken with unknown cameras, in a matter of minutes. The standard of calibration has proved to be sufficient for model-based pose recovery and tracking of vehicles.
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Several pixel-based people counting methods have been developed over the years. Among these the product of scale-weighted pixel sums and a linear correlation coefficient is a popular people counting approach. However most approaches have paid little attention to resolving the true background and instead take all foreground pixels into account. With large crowds moving at varying speeds and with the presence of other moving objects such as vehicles this approach is prone to problems. In this paper we present a method which concentrates on determining the true-foreground, i.e. human-image pixels only. To do this we have proposed, implemented and comparatively evaluated a human detection layer to make people counting more robust in the presence of noise and lack of empty background sequences. We show the effect of combining human detection with a pixel-map based algorithm to i) count only human-classified pixels and ii) prevent foreground pixels belonging to humans from being absorbed into the background model. We evaluate the performance of this approach on the PETS 2009 dataset using various configurations of the proposed methods. Our evaluation demonstrates that the basic benchmark method we implemented can achieve an accuracy of up to 87% on sequence ¿S1.L1 13-57 View 001¿ and our proposed approach can achieve up to 82% on sequence ¿S1.L3 14-33 View 001¿ where the crowd stops and the benchmark accuracy falls to 64%.
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Garment information tracking is required for clean room garment management. In this paper, we present a camera-based robust system with implementation of Optical Character Reconition (OCR) techniques to fulfill garment label recognition. In the system, a camera is used for image capturing; an adaptive thresholding algorithm is employed to generate binary images; Connected Component Labelling (CCL) is then adopted for object detection in the binary image as a part of finding the ROI (Region of Interest); Artificial Neural Networks (ANNs) with the BP (Back Propagation) learning algorithm are used for digit recognition; and finally the system is verified by a system database. The system has been tested. The results show that it is capable of coping with variance of lighting, digit twisting, background complexity, and font orientations. The system performance with association to the digit recognition rate has met the design requirement. It has achieved real-time and error-free garment information tracking during the testing.
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Calibrated cameras are an extremely useful resource for computer vision scenarios. Typically, cameras are calibrated through calibration targets, measurements of the observed scene, or self-calibrated through features matched between cameras with overlapping fields of view. This paper considers an approach to camera calibration based on observations of a pedestrian and compares the resulting calibration to a commonly used approach requiring that measurements be made of the scene.
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In this paper we report the degree of reliability of image sequences taken by off-the-shelf TV cameras for modeling camera rotation and reconstructing 3D structure using computer vision techniques. This is done in spite of the fact that computer vision systems usually use imaging devices that are specifically designed for the human vision. Our scenario consists of a static scene and a mobile camera moving through the scene. The scene is any long axial building dominated by features along the three principal orientations and with at least one wall containing prominent repetitive planar features such as doors, windows bricks etc. The camera is an ordinary commercial camcorder moving along the axial axis of the scene and is allowed to rotate freely within the range +/- 10 degrees in all directions. This makes it possible that the camera be held by a walking unprofessional cameraman with normal gait, or to be mounted on a mobile robot. The system has been tested successfully on sequence of images of a variety of structured, but fairly cluttered scenes taken by different walking cameramen. The potential application areas of the system include medicine, robotics and photogrammetry.
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The stylistic strategies, in particular those concerning camera placement and movement, of The Shield (FX, 2002-08) seem to directly fit into an aesthetic tradition developed by US cop dramas like Hill Street Blues (NBC, 1981-87), Homicide: Life on the Street (NBC, 1993-99) and NYPD Blue (ABC, 1993-2005). In these precinct dramas, decisions concerning spatial arrangements of camera and performer foreground a desire to present and react to action while it is happening, and with a minimum of apparent construction. As Jonathan Bignell (2009) has argued, the intimacy and immediacy of this stylistic approach, which has at its core an attempt at a documentary-like realism, is important to the police drama as a genre, while also being tendencies that have been taken as specific characteristics of television more generally. I explore how The Shield develops this tradition of a reactive camera style in its strategy of shooting with two cameras rather than one, with specific attention to how this shapes the presentation of performance. Through a detailed examination of the relationship between performer and camera(s) the chapter considers the way the series establishes access to the fictional world, which is crucial to the manner of police investigation central to its drama, and the impact of this on how we engage with performance. The cameras’ placement appears to balance various impulses, including: the demands of attending to an ensemble cast, spontaneous performance style, and action that is physically dynamic and involving. In a series that makes stylistic decisions around presentation of the body on-screen deliberately close yet obstructive, involving yet fleeting, the chapter explores the affect of this on the watching experience.
Resumo:
Traditionally, spoor (tracks, pug marks) have been used as a cost effective tool to assess the presence of larger mammals. Automated camera traps are now increasingly utilized to monitor wildlife, primarily as the cost has greatly declined and statistical approaches to data analysis have improved. While camera traps have become ubiquitous, we have little understanding of their effectiveness when compared to traditional approaches using spoor in the field. Here, we a) test the success of camera traps in recording a range of carnivore species against spoor; b) ask if simple measures of spoor size taken by amateur volunteers is likely to allow individual identification of leopards and c) for a trained tracker, ask if this approach may allow individual leopards to be followed with confidence in savannah habitat. We found that camera traps significantly under-recorded mammalian top and meso-carnivores, with camera traps more likely under-record the presence of smaller carnivores (civet 64%; genet 46%, Meller’s mongoose 45%) than larger (jackal sp. 30%, brown hyena 22%), while leopard was more likely to be recorded by camera trap (all recorded by camera trap only). We found that amateur trackers could be beneficial in regards to collecting presence data; however the large variance in measurements of spoor taken in the field by volunteers suggests that this approach is unlikely to add further data. Nevertheless, the use of simple spoor measurements in the field by a trained field researcher increases their ability to reliably follow a leopard trail in difficult terrain. This allows researchers to glean further data on leopard behaviour and habitat utilisation without the need for complex analysis.