Dynamic Annotation Rendering Strength for Gigapixel Images
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Solution Overview
Problem
Existing techniques for rendering annotations on large images, such as gigapixel images, face challenges with scale changes during zooming and panning, leading to issues like overly large or small text and audio playback when the associated object is not in view, resulting in a suboptimal user experience.
Innovation Solution
A system that computes the strength of annotations based on factors like distance, size, and depth relative to the view, determining whether to render and how to render annotations, including text and audio, by using a strength calculation model that adjusts rendering parameters such as volume, brightness, and size, and employs a depth map to enhance rendering precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If annotations are rendered at fixed size and volume, then rendering is simple, but annotations become unreadable or incoherent during zooming and panning
Solution Approach 1:
The system dynamically adjusts annotation rendering parameters (size, volume, brightness) based on the current view state, zoom level, and annotation strength rather than using fixed values. This allows annotations to adapt automatically to changing viewing conditions, maintaining readability while keeping the rendering process manageable through automated control.
Solution Approach 2:
The system changes multiple rendering parameters simultaneously (text size, audio volume, brightness) based on computed annotation strength and view conditions. This multi-parameter adjustment ensures annotations remain appropriate and readable across different zoom levels and viewing scenarios without manual intervention.
2Loss of information
If all annotations are rendered continuously, then information completeness is maintained, but visual and auditory overcrowding occurs
Solution Approach 1:
The system applies different rendering qualities and visibility levels to different annotations based on their computed strength and relevance to the current view. Annotations closer to the center or more relevant to the current viewpoint receive higher priority and stronger rendering, while less relevant annotations are suppressed or rendered more subtly, preventing overcrowding while preserving important information.
Solution Approach 2:
The annotation strength computation acts as an intermediary that filters and prioritizes which annotations should be rendered and to what extent. This intermediary layer processes all annotations but selectively renders only those with sufficient strength, balancing information completeness with avoidance of overcrowding.
3Stability of the object's composition
If annotation size scales with zoom level, then annotations maintain relative proportion, but annotations become too large or small at extreme zoom levels
Solution Approach 1:
The system uses dynamic scaling where annotation size adjusts based on both zoom level and annotation strength, with bounds to prevent extreme sizes. This dynamic approach maintains proportional relationships during normal zooming while adapting to extreme conditions by applying strength-based modulation and thresholding.
Solution Approach 2:
The system modifies multiple parameters including annotation size, but also adjusts volume, brightness, and visibility thresholds simultaneously. This coordinated parameter change ensures annotations remain appropriately scaled and rendered across the full range of zoom levels without becoming excessively large or small.
4Loss of information
If audio annotations play continuously, then all information is conveyed, but audio coherence deteriorates when objects are out of view
Solution Approach 1:
The system applies different audio rendering qualities to different annotations based on their strength and visibility. Annotations corresponding to visible or highly relevant objects receive stronger audio playback, while those for out-of-view objects are suppressed or played at reduced volume, maintaining audio coherence with the visual experience.
Solution Approach 2:
The annotation strength computation serves as an intermediary that controls audio playback decisions. It filters which annotations should trigger audio and at what volume, ensuring audio coherence by linking audio playback to the current relevant view rather than playing all annotations continuously.
Data Source
AI summary
Techniques are described for rendering annotations associated with an image. A view of an image maybe shown on a display, and different portions of the image are displayed and undisplayed in the view according to panning and/or zooming of the image within the view. The image may have annotations. An annotation may have a location in the image and may have associated renderable media. The location of the annotation relative to the view may change according to the panning and/or zooming. A strength of the annotation may be computed, the strength changing based the panning and/or zooming of the image. The media may be rendered according to the strength. Whether to render the media may be determined by comparing the strength to a threshold.