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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.
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] Well-researched domains of object detection include face detection and pedestrian detection.
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 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).
In humans, areas specialized for visual object recognition in the ventral stream have a more inferior location in the temporal cortex, whereas areas specialized for the visual-spatial location of objects in the dorsal stream have a more superior location in the parietal cortex. However, these two streams hypothesis, although useful, are a ...
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 ...
The ImageNet project is a large visual database designed for use in visual object recognition software research. More than 14 million [1] [2] images have been hand-annotated by the project to indicate what objects are pictured and in at least one million of the images, bounding boxes are also provided. [3]
The fusiform face area (FFA, meaning spindle-shaped face area) is a part of the human visual system (while also activated in people blind from birth [1]) that is specialized for facial recognition. [2] It is located in the inferior temporal cortex (IT), in the fusiform gyrus (Brodmann area 37).