Visual Object Recognition Task

A Visual Object Recognition Task is a perceptual recognition task that requires the recognition of a visual object in a visual input.

• Context:
  • It can range from being an Visual Object Recognition by a Living System to being a Visual Object Recognition by a Software System.
• Example(s):
  • a Face Recognition Task.
  • …
• Counter-Example(s):
  • an Auditory Recognition Task.
• See: Perceptual Inference.

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References

2017

• (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/Outline_of_object_recognition Retrieved:2017-2-9.
  • 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. Objects can even be recognized when they are partially obstructed from view. This task is still a challenge for computer vision systems. Many approaches to the task have been implemented over multiple decades.

2015

• (Patel et al., 2015) ⇒ Ankit B. Patel, Tan Nguyen, and Richard G. Baraniuk. (2015). “A Probabilistic Theory of Deep Learning.” In: arXiv:1504.00641 Journal.
  • QUOTE: A grand challenge in machine learning is the development of computational algorithms that match or outperform humans in perceptual inference tasks that are complicated by nuisance variation. For instance, visual object recognition involves the unknown object position, orientation, and scale in object recognition while speech recognition involves the unknown voice pronunciation, pitch, and speed.

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