The internal representation of solid shape with respect to vision

Koenderink, Jan J.; Doorn, Andrea J. van

doi:10.1007/bf00337644

Cited by 634 publications

(223 citation statements)

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“…For example, Kamada and Kawai [1988] attempt to minimize the number of degenerate faces in orthographic projection. Plemenos and Benayada [1996] describe a measure for goodness of views based on projected area of the model, while Roberts and Marshall [1998] compute multiple views that, combined, cover the entire surface of the model as well as possible, using an approximation of the aspect graph [Koenderink and Doorn 1979]. Scene visibility is also used for camera placement in the work of Fleishman et al [1999].…”

Section: Related Workmentioning

confidence: 99%

“…Silhouette features are believed to be the first index into the human memory of shapes [Hoffman and Singh 1997], and, as a direct result of Shannon's information theory, it was known as early as the 1950's that edges and contours contain a wealth of information about a 3D shape [Attneave 1954;Koenderink and Doorn 1979]. a 4 : Silhouette length.…”

Section: Attributes Of Viewsmentioning

confidence: 99%

“…Different views are not equally effective at revealing shape, and people express clear preferences for some views over others [Blanz et al 1999]. Object recognition and understanding depends on both view-independent properties [Biederman 1987] and view-dependent features [Koenderink and Doorn 1979]. Researchers have proposed a variety of measures for view point preference, for example viewpoint entropy [Vázquez et al 2001], silhouette stability [Gooch et al 2001], mesh saliency [Lee et al 2005], and symmetry [Podolak et al 2006].…”

Section: Introductionmentioning

confidence: 99%

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Perceptual models of viewpoint preference

et al. 2011

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The question of what are good views of a 3D object has been addressed by numerous researchers in perception, computer vision, and computer graphics. This has led to a large variety of measures for the goodness of views as well as some special-case viewpoint selection algorithms. In this article, we leverage the results of a large user study to optimize the parameters of a general model for viewpoint goodness, such that the fitted model can predict people's preferred views for a broad range of objects. Our model is represented as a combination of attributes known to be important for view selection, such as projected model area and silhouette length. Moreover, this framework can easily incorporate new attributes in the future, based on the data from our existing study. We demonstrate our combined goodness measure in a number of applications, such as automatically selecting a good set of representative views, optimizing camera orbits to pass through good views and avoid bad views, and trackball controls that gently guide the viewer towards better views.

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Section: Related Workmentioning

confidence: 99%

Section: Attributes Of Viewsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Perceptual models of viewpoint preference

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“…[2] R. T. Chin and C. R. Dyer, "Model-based recognition in robot vision", ACM Computing, 18(1):67-108, March 1986.…”

Section: Bibliographymentioning

confidence: 99%

“…When a very large number of objects is to be recognized hypothesis and tests methods are frequently employed [9], [10], [11], [12]. CAD-based object recognition is currently studied [3], [13], [14], [15], [16], while algorithms have been designed using topologically equivalent classes called aspect graphs [17], [18], [19], [20], [21], [22], [23].…”

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Contour-shape based reconstruction of fragmented, 1600 BC wall paintings

Papaodysseus

Panagopoulos

Exarhos

et al. 2002

IEEE Trans. Signal Process.

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In this paper a novel general methodology is introduced for the computer-aided reconstruction of the magnificent wall-paintings of the Greek island Thera (Santorini), painted in the middle of the second millennium BC. These wall-paintings are excavated in fragments and, as a result, their reconstruction is a painstaking and a time-consuming process. Therefore, in order to facilitate and speed up this process a proper system has been developed based on the introduced methodology. According to this methodology each fragment is photographed, its picture is introduced to the computer, its contour is obtained and subsequently all fragments contours are compared in a manner proposed herein. Both the system and the methodology presented here, extract the maximum possible information from the contour shape of fragments of an arbitrary initially unbroken plane object, to point out possible fragments matching. This methodology has been applied to two excavated fragmented wall-paintings consisting of 262 fragments, with full success but most important it has been used to reconstruct, for the first time, unpublished wall-paintings parts from a set of 936 fragments. 2 A. INTRODUCTION-PROBLEM DESCRIPTIONThe discovery of the wall-paintings at Akrotiri of the Greek island Thera (Santorini), is of outstanding importance for human knowledge of the early Aegean world and not only. According to prominent archaeologists these wall-paintings rank alongside the greatest archaeological discoveries.The late professor Marinatos originated the excavations, which are now successfully continued by Professor Christos Doumas. As with the treasures of Pompeii and Herculaneum, the wall-paintings of Thera were preserved due to the seal of the pumice from the great eruption of a volcano [1]. As a rule, the walls decorated with paintings no longer survive. They collapsed together with their painted coat before the volcanic eruption, due to particularly strong earthquakes. Thus, a single painting is usually scattered into many fragments mixed with the fragments of other wall-paintings, too. The restoration of the wall-paintings from the fragments is a very painstaking and time consuming process frequently demanding many months or even years of dedicated, experienced personnel work for a single wallpainting restoration. Therefore, the development of a system that will contribute to the automatic restoration of these wall-paintings is of fundamental importance for this archaeological research, but for many others too, which face the problem of an image reconstruction from excavated fragments.Each excavated wall-painting fragment after being cleaned, is being photographed with a very strict protocol, so that very similar illumination conditions, a fixed distance of the fragment plane from the camera focus and minimal photo distortion are ensured. Subsequently, the obtained image is processed and eventually each photographed fragment is embedded into a white background frame, which we call the absolute frame of reference of the specific fragmen...

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Using geometrical information for accurate scene understanding in an artificial vision system

Tambouratzis¹

1996

Int J of Intelligent Sys

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The internal representation of solid shape with respect to vision

Cited by 634 publications

References 9 publications

Perceptual models of viewpoint preference

Perceptual models of viewpoint preference

Contour-shape based reconstruction of fragmented, 1600 BC wall paintings

Using geometrical information for accurate scene understanding in an artificial vision system

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