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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 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.
Shape Recognition Technology (SRT) in people counter systems differentiating human beings (head and shoulder patterns) from objects. Human activity recognition - deals with recognizing the activity from a series of video frames, such as, if the person is picking up an object or walking.
The two-streams hypothesis is a model of the neural processing of vision as well as hearing. [1] The hypothesis, given its initial characterisation in a paper by David Milner and Melvyn A. Goodale in 1992, argues that humans possess two distinct visual systems. [2]
Bruce & Young Model of Face Recognition, 1986. One of the most widely accepted theories of face perception argues that understanding faces involves several stages: [7] from basic perceptual manipulations on the sensory information to derive details about the person (such as age, gender or attractiveness), to being able to recall meaningful details such as their name and any relevant past ...
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 ...
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]
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).