Recognition-by-components: a theory of human image understanding.

@article{Biederman1987RecognitionbycomponentsAT,
  title={Recognition-by-components: a theory of human image understanding.},
  author={Irving Biederman},
  journal={Psychological review},
  year={1987},
  volume={94 2},
  pages={
          115-147
        }
}
  • I. Biederman
  • Published 1 April 1987
  • Computer Science
  • Psychological review
The perceptual recognition of objects is conceptualized to be a process in which the image of the input is segmented at regions of deep concavity into an arrangement of simple geometric components, such as blocks, cylinders, wedges, and cones. The fundamental assumption of the proposed theory, recognition-by-components (RBC), is that a modest set of generalized-cone components, called geons (N £ 36), can be derived from contrasts of five readily detectable properties of edges in a two… 
Computational Approaches to Shape Constancy
The appearance of a three-dimensional object (that is, the pattern formed by its projection onto the retina of an eye or onto the imaging plane of a camera) depends on the point of view of the
Three-dimensional object recognition is viewpoint dependent
The human visual system is faced with the computationally difficult problem of achieving object constancy: identifying three-dimensional (3D) objects via two-dimensional (2D) retinal images that may
Object Recognition: Theories
On the Future of Object Recognition: The Contribution of Color
Cognitive theories of object recognition have traditionally emphasized structural components (Biederman, 1987; Grossberg & Mingolla, 1985). The idea that object recognition is largely driven by shape
Parts of Visual Form: Computational Aspects
TLDR
Computational support for the limb-based and neck-based parts is presented by showing that they are invariant, robust, stable and yield a hierarchy of parts.
Metric invariance in object recognition: a review and further evidence.
TLDR
Recent priming experiments in which the effects of a prior brief presentation of an image on its subsequent recognition are assessed indicate that the invariance is complete: the magnitude of visual priming is not affected by a change in position, size, orientation in depth, or the particular lines and vertices present in the image, as long as representations of the same components can be activated.
Neural and psychophysical analysis of object and face recognition
A number of behavioral phenomena distinguish the recognition of faces and objects, even when members of the set of objects are highly similar. Because faces have the same parts in approximately the
Object Discrimination Based on Depth-from-Occlusion
TLDR
A model of how objects can be visually discriminated based on the extraction of depth-from-occlusion is presented, which accounts for human perceptions of illusory contour stimuli.
Surface versus edge-based determinants of visual recognition
Shape Recognition in Mind, Brain, and Machine
TLDR
The manner in which the model’s performance degrades due to accidental synchrony produced by an excess of phase sets suggests a basis for a theory of visual attention.
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 130 REFERENCES
Human image understanding: Recent research and a theory
  • I. Biederman
  • Computer Science
    Comput. Vis. Graph. Image Process.
  • 1985
Reference frames and shape perception
Recovery of the Three-Dimensional Shape of an Object from a Single View
Analysis of occluding contour
  • D. Marr
  • Mathematics
    Proceedings of the Royal Society of London. Series B. Biological Sciences
  • 1977
Almost nothing can be deduced about a general three-dimensional surface given only its occluding contours in an image, yet contour information is easily and effectively used by us to infer the shape
Representation and recognition of the spatial organization of three-dimensional shapes
  • D. Marr, H. Nishihara
  • Computer Science
    Proceedings of the Royal Society of London. Series B. Biological Sciences
  • 1978
The human visual process can be studied by examining the computational problems associated with deriving useful information from retinal images. In this paper, we apply this approach to the problem
Visual routines
Invariant surface characteristics for 3D object recognition in range images
  • P. Besl, R. Jain
  • Computer Science
    Comput. Vis. Graph. Image Process.
  • 1986
...
1
2
3
4
5
...