To What Extent Do Unique Parts Influence Recognition Across Changes in Viewpoint?

Abstract

We investigated how varying the number of unique parts within an object influences recognition across changes in viewpoint The stimuli were shaded objects composed of five three-dimensional volumes linked end to end with varying connection angles Of the five volumes, zero, one, three, or five were qualitatively distinct (e g, brick vs cone), the rest being tubes Sequential-matching and naming tasks were used to assess the recognition of these stimuli over rotations in depth Three major results stand out First, regardless of the number of distinct parts, there was increasingly poorer recognition performance with increasing change in viewpoint Second, the impact of viewpoint change for objects with one unique part was less than that for the other objects Third, additional parts beyond a single unique part produced strong viewpoint dependency comparable to that obtained for objects with no distinct parts Thus, visual recognition may be explained by a view-based theory in which viewpoint-specific representations encode both quantitative and qualitative features.

Get full access to this article

View all access options for this article.

References

Brederman

(1987). Recognition by-components A theory of human image understanding. Psychological, 94, 115–147.

Brederman

Bar

(1995, November) One shot viewpoint invariance with nonsense objects . Paper presented at the annual meeting of the Psychonomic Scoiety, Los Angeles.

Biederman

Cooper

E.E.

(1991). Evidence for complete translational and reflectional invarrance in visual object priming Perception, 20, 585–593.

Biederman

Gerhardstein

P. C.

(1993). Recognizing depth-rotated objects Evidence and conditions for three-dimensional viewpoint invariance Journal of Experimental Psychology Human Perception and Performance, 19, 1162–1182.

Brederman

Gerhardstein

P.C.

(1995). Viewpoint-dependent mechanism in visual object recognition Reply to Tarr and Bulthoff (1995). Journal of Experimental Psychology Human Perception and Performance, 21, 1506–1514.

Bulthoff

H.H.

Edelman

(1992). Psychophysical support for a two-dimensional view interpolation theory of object recognition Proceedings of the National Academy of Science USA, 89, 60–64.

Bulthoff

H. H.

Edelman

S. Y.

Tarr

M. J.

(1995). How are three dimensional objects represented in the brain?Cerebral Cortex, 5, 247–260.

Cohen

Kubovy

(1993). Mental rotation mental representation and flat slopes. Cognitive Psychology, 25, 351–382.

Cooper

L. A.

Schacter

D. L.

Ballesteros

Moore

(1992). Pruning and recognition of transformed three-dimensional object Effects of size and reflection. Journal of Experimental Psychology Learning Memory and Cognition, 18, 43–57.

10.

Edelman

Bulthoff

H.H.

(1992). Orientation dependence in the recognition of familiar and novel views of three-dimensional objects Vision Research, 32, 2385–2400.

11.

Ellis

Alllport

D. A.

(1986). Multiple levels of representation for visual objects A behavioral study In Cohn

A. G.

Thomas

J. R.

(Eds.), Artificial intelligence and its application (pp. 245–247) New York Wiley.

12.

Hayward

W. G.

Tarr

M. J.

(1995). Spatial language and spatial representation Cognition, 55, 39–84.

13.

Hoffman

Richards

(1984). Parts of recognition Cognition, 18, 65–96.

14.

Hummel

J. E.

Brederman

(1992) Dynamic binding in a neural network for shape recognition. Psychological Review, 99, 480–517.

15.

Humphrey

G.K.

Khan

S.C.

(1992). Recognizing novel views of three-dimensional objects Canadian Journal of Psychology, 46, 170–190.

16.

Liter

J.C.

(1995). Features affecting orientation invariant recognition of novel objects Unpublished doctoral dissertation University of California, Irvine.

17.

Lru

Kersten

Knill

D. C.

(1995) Sructural organization anproves objects discrimination Unpublished manuscript, University of Minnesota, Minneapolis.

18.

Marr

(1982). Vision, San Francisco Freeman.

19.

Marr

Nishihara

H. K.

(1978). Representation and recognition of the spatrial organization of three-dimensional shapes Philosophical transactions of the Royal Society of London B 200, 269–294.

20.

Palmer

S.E.

(1977). Hierarchical structure in perception representation Cognitive Science, 9, 441–474.

21.

Perrett

D.I.

Oram

M. W.

Wachsmuth

(1996). Evidence accumulation in cell population responsive to facts An account of generalization of recognition with out menial transformations Unpublished manuscript, St. Andrews University St. Andrews, Scotland.

22.

Poggio

Edelman

(1990). A network that learns to recognize three dimensional objects. Nature, 343, 263–266.

23.

Snodgrass

J. G.

Corwin

(1988) Pragmatic of measuring recognition memory Application to dementias and amnesia. Journal of Experimental Psychology General, 117, 34–50.

24.

Tarr

M.J.

(1995). Rotating objects to recognize them A case study of the role of view- point dependency in die recognition of Three-dimensional objects. Psychonomic Bulletin & Review, 2, 55–82.

25.

Tarr

M.J.

Bulthoff

H. H.

(1995). Is human object recognition better described by geon structural description or by multiple views? Comment on Biederman and Gerthardstein (1993). Journal of Experimental Psychology Human Perception and Performance, 21, 1494–1505.

26.

Tarr

M.J.

Hayward

W.G.

Gauthier

Williams

(1994, November) Geon recognition is viewpoint dependent. Paper presented at the annual meeting of the Psychonomic Society St Louis MO.

27.

Tarr

M.J.

Pinker

(1990). When does human object recognition use a viewer-centerd reference frame?Psychological Science, 1, 253–256.