METHOD AND APPARTUS FOR SELECTIVELY INTEGRATING SENSORY CONTENT
First Claim
1. A machine-implemented method, comprising in a processor:
- establishing a reference position;
establishing a physical data model at least substantially representing at least one physical entity, said physical data model being spatially dynamic in time;
establishing a notional data model at least substantially representing at least one notional entity, said notional data model being dynamic in time and non-exclusive of spatial coincidence with said physical data model;
determining an occlusion of said notional data model by said physical data model relative to said reference position, wherein a first distance along a first direction from said reference position to said physical data model is less than a second distance along a second direction from said reference position to said notional data model, said second direction being at least substantially similar to said first direction;
generating notional visual content representing at least a portion of said notional data model with at least a portion of said occlusion applied thereto;
outputting to said reference position with a see-through display said notional visual content, at least substantially registered with said physical data model.
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Accused Products
Abstract
To integrate a sensory property such as occlusion, shadowing, reflection, etc. among physical and notional (e.g. virtual/augment) visual or other sensory content, providing an appearance of similar occlusion, shadowing, etc. in both models. A reference position, a physical data model representing physical entities, and a notional data model are created or accessed. A first sensory property from either data model is selected. A second sensory property is determined corresponding with the first sensory property, and notional sensory content is generated from the notional data model with the second sensory property applied thereto. The notional sensory content is outputted to the reference position with a see-through display. Consequently, notional entities may appear occluded by physical entities, physical entities may appear to cast shadows from notional light sources, etc.
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Citations
43 Claims
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1. A machine-implemented method, comprising in a processor:
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establishing a reference position; establishing a physical data model at least substantially representing at least one physical entity, said physical data model being spatially dynamic in time; establishing a notional data model at least substantially representing at least one notional entity, said notional data model being dynamic in time and non-exclusive of spatial coincidence with said physical data model; determining an occlusion of said notional data model by said physical data model relative to said reference position, wherein a first distance along a first direction from said reference position to said physical data model is less than a second distance along a second direction from said reference position to said notional data model, said second direction being at least substantially similar to said first direction; generating notional visual content representing at least a portion of said notional data model with at least a portion of said occlusion applied thereto; outputting to said reference position with a see-through display said notional visual content, at least substantially registered with said physical data model. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A machine-implemented method, comprising in a processor:
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establishing a reference position; establishing a physical data model at least substantially representing at least one physical entity, said physical data model being spatially dynamic in time; establishing a notional data model at least substantially representing at least one notional entity, said notional data model being dynamic in time and non-exclusive of spatial coincidence with said physical data model; establishing a first sensory property from one of said physical and notional data models; determining a second sensory property, said second sensory property at least substantially corresponding with said first sensory property for another of said physical and notional data models; generating notional sensory content representing at least a portion of said notional data model with at least a portion of said second sensory property applied thereto; outputting to said reference position with a perceive-through display said notional sensory content, at least substantially registered with said physical data model. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33)
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34. The method of claim 34, wherein:
said second sensory property at least substantially represents said physical environmental phenomenon. - View Dependent Claims (35, 36, 37, 38, 39)
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40. An apparatus, comprising:
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a processor; a perceive-through display in communication with said processor; a reference position establisher comprising executable instructions instantiated on said processor, said reference position establisher being adapted to establish a reference position; a physical data model establisher comprising executable instructions instantiated on said processor, said physical data model establisher being adapted to establish a physical data model at least substantially representing at least one physical entity, said physical data model being spatially dynamic in time; a notional data model establisher comprising executable instructions instantiated on said processor, said notional data model establisher being adapted to establish a notional data model at least substantially representing at least one notional entity, said notional data model being dynamic in time and non-exclusive of spatial coincidence with said physical data model; an occlusion determiner comprising executable instructions instantiated on said processor, said occlusion determiner being adapted to determine an occlusion of said notional data model by said physical data model relative to said reference position, wherein a first distance along a first direction from said reference position to said physical data model is less than a second distance along a second direction from said reference position to said notional data model, said second direction being at least substantially similar to said first direction; an occlusion applier comprising executable instructions instantiated on said processor, said occlusion applier being adapted to apply said occlusion to said notional data model; and an outputter comprising executable instructions instantiated on said processor, said outputter being adapted to output to said reference position with said perceive-through display at least a portion of said notional data model with said occlusion applied thereto at least substantially registered with said physical data model.
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41. An apparatus, comprising:
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a processor; a see-through display in communication with said processor; a reference position establisher comprising executable instructions instantiated on said processor, said reference position establisher being adapted to establish a reference position; a physical data model establisher comprising executable instructions instantiated on said processor, said physical data model establisher being adapted to establish a physical data model at least substantially representing at least one physical entity, said physical data model being spatially dynamic in time; a notional data model establisher comprising executable instructions instantiated on said processor, said notional data model establisher being adapted to establish a notional data model at least substantially representing at least one notional entity, said notional data model being dynamic in time and non-exclusive of spatial coincidence with said physical data model; a first sensory property establisher comprising executable instructions instantiated on said processor, said first sensory property establisher being adapted to establish a first sensory property from one of said physical and notional data models; a second sensory property determiner comprising executable instructions instantiated on said processor, said second sensory property determiner being adapted to determine a second sensory property at least substantially corresponding with said first sensory property for another of said physical and notional data models; a second sensory property applier comprising executable instructions instantiated on said processor, said second sensory property applier being adapted to apply said second sensory property to said notional data model so as to generate notional sensory content therefrom; an outputter comprising executable instructions instantiated on said processor, said outputter being adapted to output to said reference position said notional sensory content with a perceive-through display at least substantially registered with said physical data model.
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42. A machine-implemented method, comprising in a processor:
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means for establishing a reference position; means for establishing a physical data model at least substantially representing at least one physical entity, said physical data model being spatially dynamic in time; means for establishing a notional data model at least substantially representing at least one notional entity, said notional data model being dynamic in time and non-exclusive of spatial coincidence with said physical data model; means for determining an occlusion of said notional data model by said physical data model relative to said reference position, wherein a first distance along a first direction from said reference position to said physical data model is less than a second distance along a second direction from said reference position to said notional data model, said second direction being at least substantially similar to said first direction; means for generating notional visual content representing at least a portion of said notional data model with at least a portion of said occlusion applied thereto; means for outputting to said reference position with a see-through display said notional visual content at least substantially registered with said physical data model.
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43. A machine-implemented method, comprising in a processor:
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means for establishing a reference position; means for establishing a physical data model at least substantially representing at least one physical entity, said physical data model being spatially dynamic in time; means for establishing a notional data model at least substantially representing at least one notional entity, said notional data model being spatially dynamic in time and non-exclusive of spatial coincidence with said physical data model; means for establishing a first sensory property from one of said physical and notional data models; means for determining a second sensory property, said second sensory property at least substantially corresponding with said first sensory property for another of said physical and notional data models; means for generating notional sensory content representing at least a portion of said notional data model with at least a portion of said second sensory property applied thereto; means for outputting to said reference position with a perceive-through display said notional sensory content at least substantially registered with said physical data model.
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Specification