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Table 3.1: Surface properties added to scene modelling language.

in Multi-Sensory Rendering for Viewpoint-Independent Scenes.
by Jackson Pope

Table 1: Conversation/Opera Scenes Model (COSM) States

in CONVERSATIONAL INTERACTIVITY IN SLOW-MOTION: A COMPARISON OF PHONE DIALOGUES AND OPERA SCENES
by Peter Reichl, Florian Hammer

Table 1: Conversation/Opera Scenes Model (COSM) States

in CONVERSATIONAL INTERACTIVITY IN SLOW-MOTION: A COMPARISON OF PHONE DIALOGUES AND OPERA SCENES
by Peter Reichl, Florian Hammer

Table 2: Peg-to-a-slot scene: Generated hypotheses. Scene Scene Model Sets Generated

in Localizing a Polyhedral Object in a Robot Hand by Integrating Visual and Tactile Data
by Michael Boshra, Hong Zhang
"... In PAGE 28: ... In each run, the sensory data are randomly perturbed, according to the bounded-error model outlined above, assuming t = 5 , rt = 5 mm, dt = 0:75 mm, and rv = 1 pixel. The results obtained in all runs are averaged and summarized in Table2 . Columns in this table are: 1.... In PAGE 29: ... Filtered Model Sets 2: average number of model sets, per scene set, that are accepted by both the volumetric constraints and those on transformation-invariant attributes 6. Generated Hypotheses: average number of generated hypotheses, per scene set From Table2 , we can observe the following: 1. The ltering techniques are very e ective in reducing the number of model junctions passed to the matcher.... ..."

Table 4: First real scene: Generated hypotheses. Scene Scene Model Sets Generated

in Localizing a Polyhedral Object in a Robot Hand by Integrating Visual and Tactile Data
by Michael Boshra, Hong Zhang
"... In PAGE 33: ... To test the system performance in the S-patch case, we also consider the center of the sensor as an S-patch of negligible dimensions (notice that it lies inside the tactile polygon). Localization results are shown in Table4 . From this table, we can draw conclusions similar to those reached in the simulation experiments.... ..."

Table 1: Summary of the elements of fuzzy conceptual graphs for scene models and input images.

in Fuzzy Conceptual Graphs for Matching Images of Natural Scenes
by Philippe Mulhem, Wee Kheng Leow, Yoong Keok Lee

Table I. Refresh rate of the haptic scene whit different models.

in CybHaptics: A Class for Haptics Support in Virtual Reality Systems
by Daniel F. L. Souza, Ronei M. Moraes, Liliane S. Machado

Table 3: Total number of scene graph nodes and the number of redundant nodes in the models, as well as the accomplished scene graph reduction.

in Jupiter: a toolkit for interactive large model visualization
by Dirk Bartz, Dirk Staneker, Wolfgang Straßer, Brian Cripe, Tom Gaskins, Kristann Orton, Michael Carter, Andreas Johannsen, Jeff Trom 2001
"... In PAGE 4: ... In the new version of Jupiter, no occlusion tests are performed on redundant nodes. Table3 shows how many nodes in the scene graph of a model are redundant. Note that not all redundant nodes are visited, since many of them are already culled if one of their parent nodes is already occluded.... ..."
Cited by 1

Table 3: Scene-based time series models for I frames.

in On the Characterization of VBR MPEG Streams
by Marwan Krunz, Satish K. Tripathi 1997
Cited by 42

Table 1: Model complexity overview: The number of triangles and objects, and the depth of the scene graph for each model are listed.

in Jupiter: a toolkit for interactive large model visualization
by Dirk Bartz, Dirk Staneker, Wolfgang Straßer, Brian Cripe, Tom Gaskins, Kristann Orton, Michael Carter, Andreas Johannsen, Jeff Trom 2001
"... In PAGE 4: ... We base the performance measurements on a set of reasonable large polygonal models from mechanical engineering. These mod- els are described in Table1 . Other examples can be found in Fig- ure 6.... ..."
Cited by 1
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