Object recognition

Object recognition in computer vision is the task of finding a given object 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 / scale 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 in general.

Approaches based on CAD-like object models

Edge detection, primal sketch, Marr, Mohan and Nevatia, Lowe, Faugeras

Recognition by parts

Binford (generalized cylinders), Biederman (geons), Dickinson, Forsyth and Ponce

Appearance-based methods

Histograms: Swain and Ballard, Schiele and Crowley, Schneiderman and Kanade, Linde and Lindeberg, Koenderink and van Doorn

Scale-invariant feature transform

David Lowe pioneered the computer vision approach to extracting and using scale-invariant SIFT features from images to perform reliable object recognition.

Applications

Object recognition methods has the following applications: Image panoramas
Image watermarking
Global robot localization

Surveys

Daniilides and Eklundh, Edelman

Translation

The phrase "Object recognition" occurs as such in the following languages: English, Italian.

Translation(s) in other languages: German: Objekterkennung, Dutch: Objectherkenning.