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It is often emphasised that sensory processes, especially vision, must allow animals to recognise real objects in the natural world and that this requires complex information processing (Bernays & Wcislo, 1996; Logothetis & Sheinberg, 1996; Riesenhuber and Poggio, 2000; Tarr and Cheng, 2003).

“Imagine waiting for incoming passengers at the arrival gate at the airport. Your visual system can easily find faces and identify whether one of them is your friend’s. As with other tasks that our brain does effortlessly, visual recognition has turned out to be difficult for computers. In its general form, it is a very difficult computational problem, which is likely to be significantly involved in eventually making intelligent machines. Not surprisingly, it is also an open and key problem for neuroscience.

The main computational difficulty is the problem of variability. A vision system needs to generalize across huge variations in the appearance of an object such as a face, due for instance to viewpoint, illumination or occlusions. At the same time, the system needs to maintain specificity. It is important here to note that an object can be recognized at a variety of levels of specificity: a cat can be recognized as “my cat” on the individual level, or more broadly on the categorical level as “cat”, “mammal”, “animal” and so forth. (Riesenhuber and Poggio, 2000; p. 1199)

"The ability to readily adapt to novel situations requires something beyond storing specific stimulus-response associations. Instead, many animals can detect basic characteristics of events and store them as generalized classes. Because these representations are abstracted beyond specific details of sensory inputs and motor outputs, they can be easily generalized and adapted to new circumstances. Explorations of neural mechanisms of sensory processing and motor output have progressed to the point where studies can begin to address the neural basis of abstract, categorical representations. Recent studies have revealed their neural correlates in various cortical areas of the non-human primate brain." Abstract of Miller et al., (2003)

“Visual recognition of objects is an impressively difficult problem that biological systems solve effortlessly.” (Tarr and Cheng, 2003)

“Visual object recognition is of fundamental importance to most animals.” (Logothetis and Sheinberg, 1996)

Categorization and pattern recognition, involving grouping of sets of stimuli in functional relations to responses, appear to be consequences of perceptual learning. (Overall conclusion, p. 4 of handout)

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Comparative anatomy and physiology of the visual system (e.g. Walker, 1985 pp 266-286)
  • Vertebrate eye displays more uniformity of structure than any other organ.

  • Fish and amphibians focus by moving the lens backwards and forwards. Higher vertebrates thicken lens by tightening or relaxing muscles.

  • Rats (Leonard and McNaugton, 1990) are widely believed to have poor vision (especially albinos which can resolve 0.38 cycles per degree; pigmented rats 1.2 cycles per degree of visual angle: humans about 60 cycles per degree). This allows us to detect sharp edges, but natural scenes have low spatial frequencies, where contrast sensitivity is better in rats than in primates. Rats' visual cortex is less comparable to that of primates (Girman et al,1999) than is the equivalent forebrain area in birds (Pettigrew and Konishi, 1976; Nieder & Wagner 1999; Shimizu & Bowers, 1999: see more material on bird brains.).

  • Rats are also good at sound localization and odour recognition

  • Human retina has 1M ganglion cells and 125M rods and cones. (but in fovea almost every receptor represented in optic nerve

  • "area" is high concentration of cones "fovea" a depression

  • Pigeon and sparrow only one fovea, but (e.g.) eagles hawks, swallows and terns have two

  • Hawk Buteo buteo has fovea with 8 times the density of cones in human fovea. Even the non-foveal parts of retina should have twice the resolving power of human vision. Many birds have ultra-violet vision (Hunt et al, 1998). However color sensitivity and visual acuity in pigeons is roughly similar to the human equivalents (Hodos et al, 1985; Roberts (1998, p32)

  • on p 256 of Walker (1987) I say pigeons have 5 different colours of oil droplet filters for their cones, and 3 different visual pigments (red, green, blue). BUT more accurate to say at least 5 types of oil droplet and 4 pigments ( Bowmaker et al, 1997; Bowmaker, 1998 : See Tovée, 1992 Nov Psychologist for Old World and new World monkeys) (tetra=4; penta=5)