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This theory proposes that object recognition lies on a viewpoint continuum where each viewpoint is recruited for different types of recognition. At one extreme of this continuum, viewpoint-dependent mechanisms are used for within-category discriminations, while at the other extreme, viewpoint-invariant mechanisms are used for the categorization ...
The recognition-by-components theory, or RBC theory, [1] is a process proposed by Irving Biederman in 1987 to explain object recognition. According to RBC theory, we are able to recognize objects by separating them into geons (the object's main component parts). Biederman suggested that geons are based on basic 3-dimensional shapes (cylinders ...
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.
Recognition memory, a subcategory of explicit memory, is the ability to recognize previously encountered events, objects, or people. [1] When the previously experienced event is reexperienced, this environmental content is matched to stored memory representations, eliciting matching signals. [2]
The ventral stream is associated with object recognition and form representation. Also described as the "what" stream, it has strong connections to the medial temporal lobe (which is associated with long-term memories), the limbic system (which controls emotions), and the dorsal stream (which deals with object locations and motion).
Geons are the simple 2D or 3D forms such as cylinders, bricks, wedges, cones, circles and rectangles corresponding to the simple parts of an object in Biederman's recognition-by-components theory. [1] The theory proposes that the visual input is matched against structural representations of objects in the brain.
It is widely used in computer vision tasks such as image annotation, [2] vehicle counting, [3] activity recognition, [4] face detection, face recognition, video object co-segmentation. It is also used in tracking objects , for example tracking a ball during a football match, tracking movement of a cricket bat, or tracking a person in a video.
In a similar way, certain particular patches and regions of the cortex are more involved in face recognition than other object recognition. Some studies tend to show that rather than the uniform global image, some particular features and regions of interest of the objects are key elements when the brain needs to recognise an object in an image.