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Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different view points, in many different sizes and scales or even when they are translated or rotated.
The algorithms for solving this problem are specialized for locating a single pre-identified object, and can be contrasted with algorithms which operate on general classes of objects, such as face recognition systems or 3D generic object recognition. Due to the low cost and ease of acquiring photographs, a significant amount of research has ...
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]
All detection techniques are based on modelling the background of the image, i.e. set the background and detect which changes occur. Defining the background can be very difficult when it contains shapes, shadows, and moving objects. In defining the background, it is assumed that the stationary objects could vary in color and intensity over time.
Visual object recognition refers to the ability to identify the objects in view based on visual input. One important signature of visual object recognition is "object invariance", or the ability to identify objects across changes in the detailed context in which objects are viewed, including changes in illumination, object pose, and background context.
A stereoscope presents 2D images of the same object from slightly different angles to the left eye and the right eye, allowing the viewer to reconstruct the original object via binocular disparity. When viewed with the proper vergence, an autostereogram does the same, the binocular disparity existing in adjacent parts of the repeating 2D patterns.
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Form perception is the recognition of visual elements of objects, specifically those to do with shapes, patterns and previously identified important characteristics. An object is perceived by the retina as a two-dimensional image, [1] but the image can vary for the same object in terms of the context with which it is viewed, the apparent size of the object, the angle from which it is viewed ...