Texture perception Lavanya Sharan February 23 rd 2011

Texture perception Lavanya Sharan February 23 rd, 2011

Typical texture perception display Image source: Landy & Graham (2004)

Typical texture perception display Image source: VPfa. CGP Fig 8. 5

Typical texture perception display Image source: VPfa. CGP Fig 8. 5 These are examples of texture segregation/segmentation tasks. Similar tasks in visual search (e. g. , find a T among Ls)

Explaining performance at these tasks The ‘back pocket’ model. Image source: Landy & Graham (2004)

‘Back pocket’/LNL/FRF/Second-order model etc. Input After 1 st stage After 2 nd stage Output Image source: Landy & Graham (2004)

‘Back pocket’/LNL/FRF/Second-order model etc. Lots of work on these models. Not tied to specific features (e. g. , line terminations). Explain performance on many texture segregation tasks. Biological plausibility. Image source: Landy & Graham (2004)

For example, Malik & Perona (1990) Image source: VPfa. CGP Fig 8. 3

For example, Bergen & Adelson (1988)

Back pocket model works on most lab stimuli. Image source: Ben-Shahar 2006

An failure case for the back pocket model. Textures Manual annotations Image source: Ben-Shahar 2006 The orientation gradient is negligible across the perceptually salient boundaries.

Lab stimuli vs. Real world stimuli Image source: Landy & Graham (2004) Image source: VPfa. CGP Fig 8. 2 Lots of psychophysics. Hardly any psychophysics. Many computational models of perception. Very few computational models of perception (mostly in computer vision).

Modeling texture appearance (Portilla & Simoncelli 2001) • Like Heeger & Bergen, impose constraints iteratively. • Four classes of constraints. Each set adds something about real world texture appearance. • Analytical model (as opposed to patch-based models) allows a framework for understanding texture perception.

Shape from texture Under assumption of isotropic texture patterns, one can estimate slant and tilt of surfaces. Image source: VPfa. CGP Fig 8. 7

Slant, tilt & perspective interact to produce texture distortions Image source: Todd et al. 2005

What about real world images? Torralba & Oliva (2002)

Summary ✓ Most perceptual studies think of texture as black-and-white simple shapes. ✓ We have learnt a lot from these stimuli. ✓ Time to examine real-world textures. Some methods to manipulate these exist (e. g. , computer vision methods). ✓ Real world texture overlaps with real world materials. More next time.