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Duration of visible persistence drifting with a pattern

Duration of visible persistence drifting with a pattern. Shin’ya Nishida NTT Communication Science Laboratories NTT Corporation, Japan nishida @ brl.ntt.co.jp. Visible persistence.

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Duration of visible persistence drifting with a pattern

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  1. Duration of visible persistence drifting with a pattern Shin’ya Nishida NTT Communication Science Laboratories NTT Corporation, Japan nishida@brl.ntt.co.jp

  2. Visible persistence • A visual stimulus continues to be visible for some time after its offset due to sluggish temporal response of visual neurones • Seen at the stimulated retinal location

  3. Stationary pattern seen through moving slits • Retinal persistence enables us to see an integrated image of successively presented patterns.

  4. Moving pattern seen through stationary slits • Non-retinal visible persistence whose retinal position drifts along with the pattern movement !?

  5. Visible persistence drifting with a pattern T1

  6. Visible persistence drifting with a pattern T2

  7. Visible persistence drifting with a pattern T3

  8. Visible persistence drifting with a pattern T4

  9. Multi-slit view • Aperture viewing / Anorthoscopic effect • Single aperture (Park’s camel) Zöllner (1862); Parks (1965) • Multiple apertures Burr (1979); Morgan (1979); Bruno & Bertamini (1990); Kellman & Shipley (1991); Mateeff et al. (1993) • A technique used for an electric signboard [Betagraph / PoleVision, (AVIX inc)] that shows horizontally moving characters in an array of vertical LED lines.

  10. Underlying mechanism of multi-slit view • Direction-selective pattern analysis (e.g., Burr et al, 1986) • Pattern (orientation and spatial frequency) selectivity of direction-selective neurons in the early visual cortex is used for the analysis of pattern in motion. • Spatial pattern information is temporally integrated over motion trajectory. • Supporting evidence • Direction (and speed) selective masking (Nishida, VSS’02) • Direction-selective adaptation (Nishida, VSS’02) • Pattern interpolation beyond spatial Nyquist frequency limit (Nishida, ACV’02)

  11. Same direction = Strong masking Noise Letter Noise Letter Direction selectivity of noise masking • Inter-slit areas were filled with a random noise mask that coherently moved in the direction same as, or opposite to, the letter movement. • Stronger masking effect for noise moving in the same direction. Time 50% 100%

  12. Opposite direction = Weak masking Noise Letter Noise Letter Direction selectivity of noise masking • Inter-slit areas were filled with a random noise mask that coherently moved in the direction same as, or opposite to, the letter movement. • Stronger masking effect for noise moving in the same direction. Time 50% 100%

  13. Nyquist frequency Pattern interpolation beyond spatial Nyquist frequency limit Correlation coefficient No slit With slit Vertical frequency Vertical frequency Horizontal frequency Horizontal frequency Each based on 6,000 trials (12,000 responses) by three subjects 1 cycle=1/32’(slit sampling frequency)

  14. Spatiotemporal receptive field & Persistence Non-direction selective sensors Direction selective sensors Space Space Time Time • Retinal persistence • Drifting persistence

  15. Purpose • To estimate the duration of drifting visible persistence (size of temporal window) • Is it comparable to the duration of retinal persistence? • Is it constant or variable against speed change? • How to measure? • Increase in the effective slit width (due to blur) is estimated from the performance of letter recognition. • Persistence duration is computed from the effective slit width and stimulus speed.

  16. Apparatus & Stimulus • VSG2/5 + Clinton monoray monitor • DP104 fast-phosphor • Refresh rate: 200 Hz • 2 min/pixel at the distance of 80.6 cm • Two sets of letters moved in opposite directions (to exclude the effects of tracking eye movement). Motion direction (R/L or L/R) was randomly determined. • Uppercase letters (64 point Arial font) of a given alphabet (excluding IJQMWZ) were shown at irregular positions and orientations (to reduce the effects of sampling phase). 58 cd/m2 Fixation point 0 cd/m2 116 cd/m2 4.3° 17.1°

  17. Methods • Parameters • Exposure duration : 320 ms (64 frames) • Slit width : 2 min (1 pixel) (except for the fat slit condition) • Drift speed : 1.67 (1 pixel/4 frames) - 6.67 deg/s (1 pixel/frame) • Procedure • Task: Identification of two letters (chance = 1/20*1/20= 0.25%) • The threshold slit interval that gave 50% correct performance was estimated by the staircase method. • Observers • The author and two naïve observers

  18. Condition (1): Letter drift (drift persistence) • Letter: Drifting • Slit: Stationary & 1 pixel width

  19. Condition (2): Slit drift (retinal persistence) • Letter: Stationary • Slit: Drifting & 1 pixel width

  20. Condition (3): Fat slit • Letter: Stationary • Slit: Stationary & Variable width

  21. Equivalent slit width Results: Observer SN C1: Letter drift C2: Slit drift C3: Fat slit

  22. Results: Observer MH C1: Letter drift C2: Slit drift Equivalent slit width C3: Fat slit

  23. Results: Observer HK C1: Letter drift C2: Slit drift Equivalent slit width C3: Fat slit

  24. blur Equivalent slit width • 2 min up to ~8 min (Letter drift)~30min (Slit drift) • Increases with drift speed SN MH HK 36.7 30.0 8.3 24.4 7.3 5.8 9.7 7.3 7.2 3.2 5.8 4.3 2 2 2

  25. Visible persistence • P : Persistence • W : Equivalent slit width • W0 : Physical slit width • S : Drift speed P = (W-W0)/S blur Drifting Retinal SN MH HK

  26. Comparison of the two persistence types • Estimated persistence is shorter for drifting persistence (~20 ms) than for retinal persistence (~68 ms). 108.8 75.5 63.3 62.9 54.0 37.7 37.8 23.1 19.3 13.3 12.0 11.6 Drifting Retinal SN MH HK

  27. As drift speed increases (1) • Estimated retinal persistence increases. • Probably not reflecting a real change in retinal persistence • Wider pattern area became visible for faster speeds Close to the limit for measuring letter identification in terms of slit interval Drifting Retinal SN MH HK

  28. As drift speed increases (2) • Estimated drifting persistence decreases (SN, HM) • Opposite to the tendency predicted by the area effect • Real reduction in drifting persistence Drifting Retinal SN MH HK

  29. Dx Dt Slow Fast Effect of speed on drifting persistence • As stimulus speed increases • Drifting blur (spatial integration area) increases • Drifting persistence (temporal integration area) decreases

  30. Conclusions • Non-retinal drifting persistence is a product of direction-selective pattern analysis that integrates pattern information over motion trajectory. • Retinal persistence is a product of pattern analysis that integrates image sequence based on temporal contiguity of successive images (Dixon & Di Lollo, 1994). • Drifting persistence in multi-slit view is estimated to be 12-38 ms (average ~20 ms), which is about 30% of retinal persistence measured by the same method. • As stimulus speed increases, drifting blur becomes wider, while drifting persistence becomes shorter.

  31. Interpolation beyond spatial sampling limit • When a static pattern is sampled by an array of vertical slit with a separation, w, correct recovery of the components whose horizontal frequency is higher than 1/2w (Nyquist frequency) is IMPOSSIBLE. • As for moving patterns, correct recovery beyond the spatial Nyquist frequency limit is POSSIBLE, if the visual system is able to select pattern information based on moving direction/speed. • Interpolation beyond the spatial Nyquist frequency limit n Direction-selective interpolation TF 1/2w SF w 1/2w 1/w

  32. How to estimate frequency response Vertical Frequency • Letter image is spatially filtered by a random-frequency-window mask. • The mask consists of a grid that divides the spatial frequency space into 32 x 32 (1024) windows. • The state of each mask window, open or close, is independently and randomly determined. • The correlation of the state of each window (0/1) with subjects’ letter response (correct/incorrect) indicates how much impact the information within that window has on the subject’s judgments. High High High Low Horizontal Frequency High cf) Ahumada & Lovell (1970), Ahumada (1996), Chubb & Nam (2000)

  33. Window open rate = 50% Vertical Frequency Horizontal Frequency

  34. Window open rate = 50% Vertical Frequency Horizontal Frequency

  35. Correlograms for letter identification Correlation coefficient No slit With slit Vertical frequency Vertical frequency Horizontal frequency Horizontal frequency Each based on 6,000 trials (12,000 responses) by three subjects 1 cycle=1/32’(slit sampling frequency)

  36. Nyquist frequency Correlograms for letter identification Correlation coefficient No slit With slit Vertical frequency Vertical frequency Horizontal frequency Horizontal frequency Each based on 6,000 trials (12,000 responses) by three subjects 1 cycle=1/32’(slit sampling frequency)

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