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159
Recognizing depth-rotated objects: Evidence and conditions for three-dimensional viewpoint invariance
- Journal of Experimental Psychology: Human Perception & Performance
, 1993
"... Five experiments on the effects of changes of depth orientation on (a) priming the naming of briefly flashed familiar objects, (b) matching individual sample volumes (geons), and (c) classifying unfamiliar objects (that could readily be decomposed into an arrangement of distinctive geons) all reveal ..."
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Cited by 214 (7 self)
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Five experiments on the effects of changes of depth orientation on (a) priming the naming of briefly flashed familiar objects, (b) matching individual sample volumes (geons), and (c) classifying unfamiliar objects (that could readily be decomposed into an arrangement of distinctive geons) all revealed immediate (i.e.. not requiring practice) depth invariance. The results can be understood in terms of 3 conditions derived from a model of object recognition (I. Biederman, 1987; J. E. Hummel & I. Biederman, 1992) that have to be satisfied for immediate depth invariance: (a) that the stimuli be capable of activating viewpoint-invariant (e.g., geon) structural descriptions (GSDs), (b) that the GSDs be distinctive (different) for each stimulus, and (c) that the same GSD be activated in original and tested views. The stimuli used in several recent experiments documenting extraordinary viewpoint dependence violated these conditions. Consider Figure 1. The viewer readily appreciates that it shows two different views of the same object, despite myriad differences in the two silhouettes and in the local image features (namely, vertices, lines, and length and curvature of these lines). In general, people typically evidence little difficulty in recognizing a familiar object when they view that object from a different perspective in depth. Is Depth Invariance Achieved Through Familiarity
SEEMORE: Combining Color, Shape, and Texture Histogramming in a Neurally Inspired Approach to Visual Object Recognition
, 1997
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View-dependent object recognition by monkeys
- Current Biology
, 1994
"... How does the brain recognize three-dimensional objects? An initial step towards the understanding of the neural substrate of visual object recognition can be taken by studying first the nature of object representation, as manifested in behavioral studies with humans or non-human primates. One fund ..."
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Cited by 129 (17 self)
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How does the brain recognize three-dimensional objects? An initial step towards the understanding of the neural substrate of visual object recognition can be taken by studying first the nature of object representation, as manifested in behavioral studies with humans or non-human primates. One fundamental question is whether these representations are object or viewer centered. We trained monkeys to recognize computer rendered objects presented from an arbitrarily chosen training view, and subsequently tested their abilityto generalize recognition for views generated by mathematically rotating the objects around any arbitrary axis.
Perceiving real-world viewpoint changes
- Psychological Science
, 1998
"... Abstract—Retinal images vary as observers move through the environment, but observers seem to have little difficulty recognizing objects and scenes across changes in view. Although real-world view changes can be produced both by object rotations (orientation changes) and by observer movements (viewp ..."
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Cited by 94 (7 self)
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Abstract—Retinal images vary as observers move through the environment, but observers seem to have little difficulty recognizing objects and scenes across changes in view. Although real-world view changes can be produced both by object rotations (orientation changes) and by observer movements (viewpoint changes), research on recognition across views has relied exclusively on display rotations. However, research on spatial reasoning suggests a possible dissociation between orientation and viewpoint. Here we demonstrate that scene recognition in the real world depends on more than the retinal projection of the visible array; viewpoint changes have little effect on detection of layout changes, but equivalent orientation changes disrupt performance significantly. Findings from our three experiments suggest that scene recognition across view changes relies on a mechanism that updates a viewer-centered representation during observer movements, a mechanism not available
Viewpointdependent mechanisms in visual object recognition: Reply to Tarr and Biilthoff
- Journal of Experimental Psychology: Human Perception and Performance
, 1995
"... I. Biederman and P. C. Gerhardstein (1993) demonstrated that a representation specifying a distinctive arrangement of viewpoint-invariant parts (a geon structural description, [GSD]) dramatically reduced the costs of rotation in depth. M. J. Tarr and H. H. Bulthoff (1995) attempt to make a case for ..."
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Cited by 90 (7 self)
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I. Biederman and P. C. Gerhardstein (1993) demonstrated that a representation specifying a distinctive arrangement of viewpoint-invariant parts (a geon structural description, [GSD]) dramatically reduced the costs of rotation in depth. M. J. Tarr and H. H. Bulthoff (1995) attempt to make a case for viewpoint-dependent mechanisms, such as mental rotation. Their suggestion that GSDs enjoy no special status in reducing the effects of depth rotation is contradicted by a wealth of direct experimental evidence as well as an inadvertent experiment that found no evidence for the spontaneous employment of mental rotation. Their complaint against geon theory's account of entry-level classification rests on a mistaken and unwar-ranted attribution that geon theory assumes a one-to-one correspondence between GSDs and entry-level names. GSDs provide a representation that distinguishes most entry- and subor-dinate-level classes and explains why complex objects are described as an arrangement of viewpoint-invariant parts. Consider the nonsense object in Figure 1. When first viewed, how did the reader know that the object was one never encountered previously? Why was the reader fairly
Model-Based Object Recognition - A Survey of Recent Research
, 1994
"... We survey the main ideas behind recent research in model-based object recognition. The survey covers representations for models and images and the methods used to match them. Perceptual organization, the use of invariants, indexing schemes, and match verification are also reviewed. We conclude that ..."
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Cited by 68 (1 self)
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We survey the main ideas behind recent research in model-based object recognition. The survey covers representations for models and images and the methods used to match them. Perceptual organization, the use of invariants, indexing schemes, and match verification are also reviewed. We conclude that there is still much room for improvement in the scope, robustness, and efficiency of object recognition methods. We identify what we believe are the ways improvements will be achieved. ii Contents 1. Introduction .................................................................................................................................... 1 2. Representation ................................................................................................................................ 3 2.1 What makes a good shape representation? ............................................................................ 3 2.2 The choice of coordinate system ..........................................
The objects of action and perception
- Cognition
, 1998
"... Two major functions of the visual system are discussed and contrasted. One function of vision is the creation of an internal model or percept of the external world. Most research in object perception has concentrated on this aspect of vision. Vision also guides the control of object-directed action. ..."
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Cited by 63 (1 self)
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Two major functions of the visual system are discussed and contrasted. One function of vision is the creation of an internal model or percept of the external world. Most research in object perception has concentrated on this aspect of vision. Vision also guides the control of object-directed action. In the latter case, vision directs our actions with respect to the world by transforming visual inputs into appropriate motor outputs. We argue that separate, but interactive, visual systems have evolved for the perception of objects on the one hand and the control of actions directed at those objects on the other. This ‘duplex ’ approach to high-level vision suggests that Marrian or ‘reconstructive ’ approaches and Gibsonian or ‘purposiveanimate-behaviorist’ approaches need not be seen as mutually exclusive, but rather as complementary in their emphases on different aspects of visual function. © 1998 Elsevier Science
One-shot viewpoint invariance in matching novel objects
- VISION RESEARCH 39 (1999) 2885–2899
, 1999
"... Humans often evidence little difficulty at recognizing objects from arbitrary orientations in depth. According to one class of theories, this competence is based on generalization from templates specified by metric properties (MPs), that were learned for the various orientations. An alternative clas ..."
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Cited by 53 (6 self)
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Humans often evidence little difficulty at recognizing objects from arbitrary orientations in depth. According to one class of theories, this competence is based on generalization from templates specified by metric properties (MPs), that were learned for the various orientations. An alternative class of theories assumes that non-accidental properties (NAPs) might be exploited so that even novel objects can be recognized under depth rotation. After scaling MP and NAP differences so that they were equally detectable when the objects were at the same orientation in depth, the present investigation assessed the effects of rotation on same-different judgments for matching novel objects. Judgments of a sequential pair of images of novel objects, when rendered from different viewpoints, revealed relatively low costs when the objects differed in a NAP of a single part, i.e. a geon. However, rotation dramatically reduced the detectability of MP differences to a level well below that expected by chance. NAPs offer a striking advantage over MPs for object classification and are therefore more likely to play a central role in the representation of
Class similarity and viewpoint invariance in the recognition of 3D objects
- Biological Cybernetics
, 1992
"... In human vision, the processes and the representations involved in identifying specific individuals are frequently assumed to be different from those used for basic-level classification, because classification is largely viewpoint-invariant, but identification is not. This assumption was tested in p ..."
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Cited by 52 (16 self)
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In human vision, the processes and the representations involved in identifying specific individuals are frequently assumed to be different from those used for basic-level classification, because classification is largely viewpoint-invariant, but identification is not. This assumption was tested in psychophysical experiments, in which objective similarity between stimuli (and, consequently, the level of their distinction) varied in a controlled fashion. Subjects were trained to discriminate between two classes of computer generated 3D objects, one resembling monkeys, and the other dogs. Both classes were defined by the same set of 56 parameters, which encoded sizes, shapes, and placement of the limbs, the ears, the snout, etc. Interpolation between parameter vectors of the class prototypes yielded shapes that changed smoothly between monkey and dog. Within-class variation was induced in each trial by randomly perturbing all the parameters. After the subjects reached 90% correct performa...
