Some key points affecting object recognition (but not all click on link above to see more): 

• • Context - Do you know what you are looking for or looking at? What is the background? What is the Context?

  • Familiarity - "Familiarity is a mechanism that is context-free in the sense that what one recognizes just feels familiar without spending time trying to find in what context one knows the object". Have you seen this before? How much familiarity do you have with what you are looking at?

  • Recognition Memory - "When someone sees an object, they know what the object is because they’ve seen it on a past occasion; this is recognition memory."

  • Recollection "shares many similarities with familiarity; however, it is context-dependent, requiring specific information from the inquired incident."

  • Impairments  such as (but not limited to):

    1.  visual object agnosia

    2. developmental prosopagnosia

    3. depth perception  - Click Here - Can be affected by blurry vision for example.

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Biedermans Recognition By Components Theory - Click Here 

• "The first step is edge extraction, which was described by Biederman (1987, p. 117) in the following way: "[There is] an early edge extraction stage, responsive to differences in surface characteristics namely, luminance, texture, or colour, provides a line drawing description of the object." 

• "The next step is to decide how a visual object should be segmented to establish the number of parts of components of which it consists. Biederman (1987) agreed with Marr and Nishihara (1978) that the concave parts of an object's contour are of particular value in accomplishing the task of segmenting the visual image into parts.

• The other major element is to decide which edge information from an object possesses the important characteristic of remaining invariant across different viewing angles. According to Biederman (1987), there are five such invariant properties of edges:

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1. Curvature: points on a curve.

2. Parallel: sets of points in parallel.

3. Co-termination: edges terminating at a common point.

4. Co-linearity: points in a straight line."

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• "However, we can generally recognise objects when the conditions are sub-optimal (e.g., an intervening object obscures part of the target object). According to Biederman (1987), there are various reasons why we are able to achieve object recognition in such conditions:

  1. The invariant properties (e.g., curvature; parallel lines) can still be detected even when only parts of edges can be seen.

  2. Provided that the concavities of a contour are visible, there are mechanisms allowing the missing parts of a contour to be restored.

  3. There is normally a considerable amount of redundant information available for recognising complex objects, and so they can still be identified when some of the geons or components are missing (e.g., a giraffe could be identified from its neck even if its legs were hidden from view)."

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