In Computer Vision, Image Processing, Artificial Intelligence and Neural Networks object recognition is one of the most successful applications of image or object analysis and understanding.The recognition system typically involves some sort of sensor, the use of a model database in which all the objects "models" representations are saved, and a decision-making ability.When a sensor views an object the digitized image is processed so as to represent it in the same way as the models are represented in the databases.Then a ...
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In Computer Vision, Image Processing, Artificial Intelligence and Neural Networks object recognition is one of the most successful applications of image or object analysis and understanding.The recognition system typically involves some sort of sensor, the use of a model database in which all the objects "models" representations are saved, and a decision-making ability.When a sensor views an object the digitized image is processed so as to represent it in the same way as the models are represented in the databases.Then a recognition algorithm tries to find the model to which the object best matches.For the view-based recognition, the representations take into account the appearance of the object. To achieve 3D Object recognition(3DOR) the pose of objects are also saved in the database.In general two 3DOR techniques. They are Geometric feature-based approach and Appearance- based approach.The geometric feature-based approach uses properties of shape of object i.e. lines, curves, and vertices for object recognition descriptions.But appearance-based 3DOR is the combined effects of objects shape, reflectance properties, pose and the illumination.
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