摘要 :
The research presented in this paper represents several novel conceptual contributions to the computer vision literature. In this position paper, our goal is to define the scope of computer vision analysis and discuss a new catego...
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The research presented in this paper represents several novel conceptual contributions to the computer vision literature. In this position paper, our goal is to define the scope of computer vision analysis and discuss a new categorisation of the computer vision problem. We first provide a novel decomposition of computer vision into base components which we term the axioms of vision. These are used to define researcher-level and developer-level access to vision algorithms, in a way which does not require expert knowledge of computer vision. We discuss a new line of thought for computer vision by basing analyses on descriptions of the problem instead of in terms of algorithms. From this an abstraction can be developed to provide a layer above algorithmic details. This is extended to the idea of a formal description language which may be automatically interpreted thus allowing those not familiar with computer vision techniques to utilise sophisticated methods.
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摘要 :
The research presented in this paper represents several novel conceptual contributions to the computer vision literature. In this position paper, our goal is to define the scope of computer vision analysis and discuss a new catego...
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The research presented in this paper represents several novel conceptual contributions to the computer vision literature. In this position paper, our goal is to define the scope of computer vision analysis and discuss a new categorisation of the computer vision problem. We first provide a novel decomposition of computer vision into base components which we term the axioms of vision. These are used to define researcher-level and developer-level access to vision algorithms, in a way which does not require expert knowledge of computer vision. We discuss a new line of thought for computer vision by basing analyses on descriptions of the problem instead of in terms of algorithms. From this an abstraction can be developed to provide a layer above algorithmic details. This is extended to the idea of a formal description language which may be automatically interpreted thus allowing those not familiar with computer vision techniques to utilise sophisticated methods.
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Computer vision techniques have been used for the automation of processes in the agricultural sector due to the benefits obtained such as effectiveness and quality. A clear example is the analysis of cocoa beans quality. The incre...
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Computer vision techniques have been used for the automation of processes in the agricultural sector due to the benefits obtained such as effectiveness and quality. A clear example is the analysis of cocoa beans quality. The increasing interest of computer vision in this area calls for a clear, systematic overview. In this sense, we present a systematic literature review (SLR) of computer vision algorithms to determine the quality of fermented cocoa in a six-year period: from 2013-2018. The aim of this review is to identify the techniques or computer vision algorithms used to assess fermentation index of cocoa beans for quality control, as well, the main physical and chemical characteristics of the cocoa beans identified through the computer vision algorithms. The results show that the PLS (Partial Least-Squares) algorithm is the most used for the classification of images in a statistical approach. Also, color is the physical parameter that is commonly identified through artificial vision algorithms. Meanwhile, Fat and pH are the chemical parameters most identified by FT-NIR (Fourier transform near-infrared) technology in conjunction with the chemo-metric technique.
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Binocular stereo vision is one of important branches of stereo vision. This paper first introduces a binocular stereo vision model. Then focuses on the stereo effects that can be seen through the model (i.e. the model's properties...
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Binocular stereo vision is one of important branches of stereo vision. This paper first introduces a binocular stereo vision model. Then focuses on the stereo effects that can be seen through the model (i.e. the model's properties): the method to calculate the coordinates of stereo pairs is given, properties of parallax are presented, and the stereo effects when eyes moving in the same plane which parallels with the screen are also discussed. Finally, conclusions drawn in the paper are proved by experiments. The results show that if the distance between observer and screen do not change, he won't feel the objects move away or come close when he shakes his head slightly, but he will feel the whole image is swaying. Though slight differences exist for different people, the phenomena each person sees accord with predictions we deduce from the model.
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摘要 :
Binocular stereo vision is one of important branches of stereo vision. This paper first introduces a binocular stereo vision model. Then focuses on the stereo effects that can be seen through the model (i.e. the model's properties...
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Binocular stereo vision is one of important branches of stereo vision. This paper first introduces a binocular stereo vision model. Then focuses on the stereo effects that can be seen through the model (i.e. the model's properties): the method to calculate the coordinates of stereo pairs is given, properties of parallax are presented, and the stereo effects when eyes moving in the same plane which parallels with the screen are also discussed. Finally, conclusions drawn in the paper are proved by experiments. The results show that if the distance between observer and screen do not change, he won't feel the objects move away or come close when he shakes his head slightly, but he will feel the whole image is swaying. Though slight differences exist for different people, the phenomena each person sees accord with predictions we deduce from the model.
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This paper presents some more advanced topics in image processing and computer vision, such as Principal Components Analysis, Matching Techniques, Machine Learning Techniques, Tracking and Optical Flow and Parallel Computer Vision...
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This paper presents some more advanced topics in image processing and computer vision, such as Principal Components Analysis, Matching Techniques, Machine Learning Techniques, Tracking and Optical Flow and Parallel Computer Vision using CUDA. These concepts will be presented using the open CV library, which is a free computer vision library for C/C++ programmers available for Windows, Linux Mac OS and Android platforms. These topics will be covered considering not only theoretical aspects but practical examples will be presented in order to understand how and when to use each of them.
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摘要 :
This paper presents some more advanced topics in image processing and computer vision, such as Principal Components Analysis, Matching Techniques, Machine Learning Techniques, Tracking and Optical Flow and Parallel Computer Vision...
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This paper presents some more advanced topics in image processing and computer vision, such as Principal Components Analysis, Matching Techniques, Machine Learning Techniques, Tracking and Optical Flow and Parallel Computer Vision using CUDA. These concepts will be presented using the open CV library, which is a free computer vision library for C/C++ programmers available for Windows, Linux Mac OS and Android platforms. These topics will be covered considering not only theoretical aspects but practical examples will be presented in order to understand how and when to use each of them.
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In this paper the algorithm Camera of calculation of the position and orientation coordinates of the object observed by the camera is presented. The camera is mounted above the technological station on which object appears. These ...
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In this paper the algorithm Camera of calculation of the position and orientation coordinates of the object observed by the camera is presented. The camera is mounted above the technological station on which object appears. These coordinates are calculated relative to the station frame (coordinate system associated with the technological station) or relative to base frame (coordinate system associated with the base of robot). The orientation is described by the xy- z fixed angles of rotation relative to station or base frame. In this algorithm the perspective model of camera is used. From the image on the camera matrix sensor of three characteristic points of the object are obtained 2D coordinates of these points. The location (position and orientation) of the object are calculated on the base of these coordinates. The calculated location coordinates allow the robot to automatically approach the object and carry out technological operations. For example, an object may be the car body and the technological operation sealing or welding. Creating of such algorithms is fundamental problem of computational intelligence for robots.
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摘要 :
In this paper the algorithm Camera of calculation of the position and orientation coordinates of the object observed by the camera is presented. The camera is mounted above the technological station on which object appears. These ...
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In this paper the algorithm Camera of calculation of the position and orientation coordinates of the object observed by the camera is presented. The camera is mounted above the technological station on which object appears. These coordinates are calculated relative to the station frame (coordinate system associated with the technological station) or relative to base frame (coordinate system associated with the base of robot). The orientation is described by the x-y-z fixed angles of rotation relative to station or base frame. In this algorithm the perspective model of camera is used. From the image on the camera matrix sensor of three characteristic points of the object are obtained 2D coordinates of these points. The location (position and orientation) of the object are calculated on the base of these coordinates. The calculated location coordinates allow the robot to automatically approach the object and carry out technological operations. For example, an object may be the car body and the technological operation sealing or welding. Creating of such algorithms is fundamental problem of computational intelligence for robots.
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摘要 :
In this paper the algorithm Camera of calculation of the position and orientation coordinates of the object observed by the camera is presented. The camera is mounted above the technological station on which object appears. These ...
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In this paper the algorithm Camera of calculation of the position and orientation coordinates of the object observed by the camera is presented. The camera is mounted above the technological station on which object appears. These coordinates are calculated relative to the station frame (coordinate system associated with the technological station) or relative to base frame (coordinate system associated with the base of robot). The orientation is described by the x-y-z fixed angles of rotation relative to station or base frame. In this algorithm the perspective model of camera is used. From the image on the camera matrix sensor of three characteristic points of the object are obtained 2D coordinates of these points. The location (position and orientation) of the object are calculated on the base of these coordinates. The calculated location coordinates allow the robot to automatically approach the object and carry out technological operations. For example, an object may be the car body and the technological operation sealing or welding. Creating of such algorithms is fundamental problem of computational intelligence for robots.
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