863 resultados para omnidirectional camera


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The basic idea behind improving local food security consists of two paths; first, accessibility (price, stock) and second, availability (quantity and biodiversity); both are perquisites to the provision of nutrients and a continuous food supply with locally available resources. The objectives of this thesis are to investigate if indigenous knowledge still plays an important role in traditional farming in the Minangkabau`s culture, thus supporting local food security. If the indigenous knowledge still plays a role in food culture in the Minangkabau`s culture which is linked to the matrilineal role and leads to a sound nutrition. Further, it should be tested if marantau influences traditional farming and food culture in Minangkabau`s, and if the local government plays a role in changing of traditional farming systems and food culture. Furthermore this thesis wants to prove if education and gender are playing a role in changing traditional farming system and food culture, and if the mass media affects traditional farming systems and food culture for the Minangkabau. The study was completed at four locations in West Sumatera; Nagari Ulakan (NU) (coastal area), Nagari Aia Batumbuak (NAB) (hilly area), Nagari Padang Laweh Malalo (NPLM) (lake area), Nagari Pandai Sikek (NPS) (hilly area). The rainfall ranged from 1400- 4800 mm annually with fertile soils. Data was collected by using PRA (Participatory Rural Appraisal) to investigate indigenous knowledge (IK) and its interactions, which is also combining with in depth-interview, life history, a survey using semi-structured-questionnaire, pictures, mapping, and expert interview. The data was collected from June - September 2009 and June 2010. The materials are; map of area, list of names, questionnaires, voices recorder, note book, and digital camera. The sampling method was snowball sampling which resulted in the qualitative and quantitative data taken. For qualitative data, ethnography and life history was used. For quantitative, a statistical survey with a semi-structured questionnaire was used. 50 respondents per each site participated voluntarily. Data was analyzed by performing MAXQDA 10, and F4 audio analysis software (created and developed by Philip-University Marburg). The data is clustered based on causality. The results show that; the role of IK on TFS (traditional farming system) shown on NPLM which has higher food crop biodiversity in comparison to the other three places even though it has relatively similar temperature and rainfall. This high food crop biodiversity is due to the awareness of local people who realized that they lived in unfavourable climate and topography; therefore they are more prepared for any changes that may occur. Carbohydrate intake is 100 % through rice even though they are growing different staple crops. Whereas most of the people said in the interviews that not eating rice is like not really eating for them. In addition to that, mothers still play an important role in kitchen activities. But when the agriculture income is low, mothers have to decide whether to change the meals or to feel insecure about their food supply. Marantau yields positive impact through the remittances it provides to invest on the farm. On the other hand, it results in fewer workers for agriculture, and therefore a negative impact on the transfer of IK. The investigation showed that the local government has a PTS (Padi Tanam Sabatang) programme which still does not guarantee that the farmers are getting sufficient revenue from their land. The low agricultural income leads to situation of potential food insecurity. It is evident that education is equal among men and women, but in some cases women tend to leave school earlier because of arranged marriages or the distances of school from their homes. Men predominantly work in agriculture and fishing, while women work in the kitchen. In NAB, even though women work on farmland they earn less then men. Weaving (NPS) and kitchen activity is recognized as women’s work, which also supports the household income. Mass media is not yielding any changes in TFS and food culture in these days. The traditional farming system has changed because of intensive agricultural extension which has introduced new methods of agriculture for the last three decades (since the 1980’s). There is no evidence that they want to change any of their food habits because of the mass media despite the lapau activity which allows them to get more food choices, instead preparing traditional meal at home. The recommendations of this thesis are: 1) The empowerment of farmers. It is regarding the self sufficient supply of manure, cooperative seed, and sustainable farm management. Farmers should know – where are they in their state of knowledge – so they can use their local wisdom and still collaborate with new sources of knowledge. Farmers should learn the prognosis of supply and demand next prior to harvest. There is a need for farm management guidelines; that can be adopted from both their local wisdom and modern knowledge. 2) Increase of non-agricultural income Increasing the non-agricultural income is strongly recommended. The remittances can be invested on non-agricultural jobs. 3) The empowerment of the mother. The mother plays an important role in farm to fork activities; the mother can be an initiator and promoter of cultivating spices in the backyard. Improvement of nutritional knowledge through information and informal public education can be done through arisan ibu-ibu and lapau activity. The challenges to apply these recommendations are: 1) The gap between institutions and organizations of local governments. There is more than one institution involved in food security policy. 2) Training and facilities for field extension agriculture (FEA) is needed because the rapid change of interaction between local government and farmer’s dependent on this agency.

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Die thermische Verarbeitung von Lebensmitteln beeinflusst deren Qualität und ernährungsphysiologischen Eigenschaften. Im Haushalt ist die Überwachung der Temperatur innerhalb des Lebensmittels sehr schwierig. Zudem ist das Wissen über optimale Temperatur- und Zeitparameter für die verschiedenen Speisen oft unzureichend. Die optimale Steuerung der thermischen Zubereitung ist maßgeblich abhängig von der Art des Lebensmittels und der äußeren und inneren Temperatureinwirkung während des Garvorgangs. Das Ziel der Arbeiten war die Entwicklung eines automatischen Backofens, der in der Lage ist, die Art des Lebensmittels zu erkennen und die Temperatur im Inneren des Lebensmittels während des Backens zu errechnen. Die für die Temperaturberechnung benötigten Daten wurden mit mehreren Sensoren erfasst. Hierzu kam ein Infrarotthermometer, ein Infrarotabstandssensor, eine Kamera, ein Temperatursensor und ein Lambdasonde innerhalb des Ofens zum Einsatz. Ferner wurden eine Wägezelle, ein Strom- sowie Spannungs-Sensor und ein Temperatursensor außerhalb des Ofens genutzt. Die während der Aufheizphase aufgenommen Datensätze ermöglichten das Training mehrerer künstlicher neuronaler Netze, die die verschiedenen Lebensmittel in die entsprechenden Kategorien einordnen konnten, um so das optimale Backprogram auszuwählen. Zur Abschätzung der thermische Diffusivität der Nahrung, die von der Zusammensetzung (Kohlenhydrate, Fett, Protein, Wasser) abhängt, wurden mehrere künstliche neuronale Netze trainiert. Mit Ausnahme des Fettanteils der Lebensmittel konnten alle Komponenten durch verschiedene KNNs mit einem Maximum von 8 versteckten Neuronen ausreichend genau abgeschätzt werden um auf deren Grundlage die Temperatur im inneren des Lebensmittels zu berechnen. Die durchgeführte Arbeit zeigt, dass mit Hilfe verschiedenster Sensoren zur direkten beziehungsweise indirekten Messung der äußeren Eigenschaften der Lebensmittel sowie KNNs für die Kategorisierung und Abschätzung der Lebensmittelzusammensetzung die automatische Erkennung und Berechnung der inneren Temperatur von verschiedensten Lebensmitteln möglich ist.

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In many motion-vision scenarios, a camera (mounted on a moving vehicle) takes images of an environment to find the "motion'' and shape. We introduce a direct-method called fixation for solving this motion-vision problem in its general case. Fixation uses neither feature-correspondence nor optical-flow. Instead, spatio-temporal brightness gradients are used directly. In contrast to previous direct methods, fixation does not restrict the motion or the environment. Moreover, fixation method neither requires tracked images as its input nor uses mechanical tracking for obtaining fixated images. The experimental results on real images are presented and the implementation issues and techniques are discussed.

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Enhanced reality visualization is the process of enhancing an image by adding to it information which is not present in the original image. A wide variety of information can be added to an image ranging from hidden lines or surfaces to textual or iconic data about a particular part of the image. Enhanced reality visualization is particularly well suited to neurosurgery. By rendering brain structures which are not visible, at the correct location in an image of a patient's head, the surgeon is essentially provided with X-ray vision. He can visualize the spatial relationship between brain structures before he performs a craniotomy and during the surgery he can see what's under the next layer before he cuts through. Given a video image of the patient and a three dimensional model of the patient's brain the problem enhanced reality visualization faces is to render the model from the correct viewpoint and overlay it on the original image. The relationship between the coordinate frames of the patient, the patient's internal anatomy scans and the image plane of the camera observing the patient must be established. This problem is closely related to the camera calibration problem. This report presents a new approach to finding this relationship and develops a system for performing enhanced reality visualization in a surgical environment. Immediately prior to surgery a few circular fiducials are placed near the surgical site. An initial registration of video and internal data is performed using a laser scanner. Following this, our method is fully automatic, runs in nearly real-time, is accurate to within a pixel, allows both patient and camera motion, automatically corrects for changes to the internal camera parameters (focal length, focus, aperture, etc.) and requires only a single image.

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We present a new method for rendering novel images of flexible 3D objects from a small number of example images in correspondence. The strength of the method is the ability to synthesize images whose viewing position is significantly far away from the viewing cone of the example images ("view extrapolation"), yet without ever modeling the 3D structure of the scene. The method relies on synthesizing a chain of "trilinear tensors" that governs the warping function from the example images to the novel image, together with a multi-dimensional interpolation function that synthesizes the non-rigid motions of the viewed object from the virtual camera position. We show that two closely spaced example images alone are sufficient in practice to synthesize a significant viewing cone, thus demonstrating the ability of representing an object by a relatively small number of model images --- for the purpose of cheap and fast viewers that can run on standard hardware.

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This paper presents an image-based rendering system using algebraic relations between different views of an object. The system uses pictures of an object taken from known positions. Given three such images it can generate "virtual'' ones as the object would look from any position near the ones that the two input images were taken from. The extrapolation from the example images can be up to about 60 degrees of rotation. The system is based on the trilinear constraints that bind any three view so fan object. As a side result, we propose two new methods for camera calibration. We developed and used one of them. We implemented the system and tested it on real images of objects and faces. We also show experimentally that even when only two images taken from unknown positions are given, the system can be used to render the object from other view points as long as we have a good estimate of the internal parameters of the camera used and we are able to find good correspondence between the example images. In addition, we present the relation between these algebraic constraints and a factorization method for shape and motion estimation. As a result we propose a method for motion estimation in the special case of orthographic projection.

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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).

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This paper investigates the linear degeneracies of projective structure estimation from point and line features across three views. We show that the rank of the linear system of equations for recovering the trilinear tensor of three views reduces to 23 (instead of 26) in the case when the scene is a Linear Line Complex (set of lines in space intersecting at a common line) and is 21 when the scene is planar. The LLC situation is only linearly degenerate, and we show that one can obtain a unique solution when the admissibility constraints of the tensor are accounted for. The line configuration described by an LLC, rather than being some obscure case, is in fact quite typical. It includes, as a particular example, the case of a camera moving down a hallway in an office environment or down an urban street. Furthermore, an LLC situation may occur as an artifact such as in direct estimation from spatio-temporal derivatives of image brightness. Therefore, an investigation into degeneracies and their remedy is important also in practice.

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We present an experimental study on the behavior of bubbles captured in a Taylor vortex. The gap between a rotating inner cylinder and a stationary outer cylinder is filled with a Newtonian mineral oil. Beyond a critical rotation speed (ω[subscript c]), Taylor vortices appear in this system. Small air bubbles are introduced into the gap through a needle connected to a syringe pump. These are then captured in the cores of the vortices (core bubble) and in the outflow regions along the inner cylinder (wall bubble). The flow field is measured with a two-dimensional particle imaging velocimetry (PIV) system. The motion of the bubbles is monitored by using a high speed video camera. It has been found that, if the core bubbles are all of the same size, a bubble ring forms at the center of the vortex such that bubbles are azimuthally uniformly distributed. There is a saturation number (N[subscript s]) of bubbles in the ring, such that the addition of one more bubble leads eventually to a coalescence and a subsequent complicated evolution. Ns increases with increasing rotation speed and decreasing bubble size. For bubbles of non-uniform size, small bubbles and large bubbles in nearly the same orbit can be observed to cross due to their different circulating speeds. The wall bubbles, however, do not become uniformly distributed, but instead form short bubble-chains which might eventually evolve into large bubbles. The motion of droplets and particles in a Taylor vortex was also investigated. As with bubbles, droplets and particles align into a ring structure at low rotation speeds, but the saturation number is much smaller. Moreover, at high rotation speeds, droplets and particles exhibit a characteristic periodic oscillation in the axial, radial and tangential directions due to their inertia. In addition, experiments with non-spherical particles show that they behave rather similarly. This study provides a better understanding of particulate behavior in vortex flow structures.

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The estimation of camera egomotion is a well established problem in computer vision. Many approaches have been proposed based on both the discrete and the differential epipolar constraint. The discrete case is mainly used in self-calibrated stereoscopic systems, whereas the differential case deals with a unique moving camera. The article surveys several methods for mobile robot egomotion estimation covering more than 0.5 million samples using synthetic data. Results from real data are also given

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This paper presents a vision-based localization approach for an underwater robot in a structured environment. The system is based on a coded pattern placed on the bottom of a water tank and an onboard down looking camera. Main features are, absolute and map-based localization, landmark detection and tracking, and real-time computation (12.5 Hz). The proposed system provides three-dimensional position and orientation of the vehicle along with its velocity. Accuracy of the drift-free estimates is very high, allowing them to be used as feedback measures of a velocity-based low-level controller. The paper details the localization algorithm, by showing some graphical results, and the accuracy of the system

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This paper presents an automatic vision-based system for UUV station keeping. The vehicle is equipped with a down-looking camera, which provides images of the sea-floor. The station keeping system is based on a feature-based motion detection algorithm, which exploits standard correlation and explicit textural analysis to solve the correspondence problem. A visual map of the area surveyed by the vehicle is constructed to increase the flexibility of the system, allowing the vehicle to position itself when it has lost the reference image. The testing platform is the URIS underwater vehicle. Experimental results demonstrating the behavior of the system on a real environment are presented

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When underwater vehicles navigate close to the ocean floor, computer vision techniques can be applied to obtain motion estimates. A complete system to create visual mosaics of the seabed is described in this paper. Unfortunately, the accuracy of the constructed mosaic is difficult to evaluate. The use of a laboratory setup to obtain an accurate error measurement is proposed. The system consists on a robot arm carrying a downward looking camera. A pattern formed by a white background and a matrix of black dots uniformly distributed along the surveyed scene is used to find the exact image registration parameters. When the robot executes a trajectory (simulating the motion of a submersible), an image sequence is acquired by the camera. The estimated motion computed from the encoders of the robot is refined by detecting, to subpixel accuracy, the black dots of the image sequence, and computing the 2D projective transform which relates two consecutive images. The pattern is then substituted by a poster of the sea floor and the trajectory is executed again, acquiring the image sequence used to test the accuracy of the mosaicking system

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Mosaics have been commonly used as visual maps for undersea exploration and navigation. The position and orientation of an underwater vehicle can be calculated by integrating the apparent motion of the images which form the mosaic. A feature-based mosaicking method is proposed in this paper. The creation of the mosaic is accomplished in four stages: feature selection and matching, detection of points describing the dominant motion, homography computation and mosaic construction. In this work we demonstrate that the use of color and textures as discriminative properties of the image can improve, to a large extent, the accuracy of the constructed mosaic. The system is able to provide 3D metric information concerning the vehicle motion using the knowledge of the intrinsic parameters of the camera while integrating the measurements of an ultrasonic sensor. The experimental results of real images have been tested on the GARBI underwater vehicle

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Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position