3D Image Visualization Using Camera Pose and Depth
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Solution Overview
Problem
Current photo management applications lack the ability to generate and utilize 3D information for organizing, visualizing, and navigating digital images, resulting in a static and unengaging display experience.
Innovation Solution
The techniques involve generating 3D information by identifying and comparing visual word frequencies between images, using structure from motion (SfM) to create 3D representations, and employing 3D attributes like camera pose and position to organize and display images in a dynamic and interactive manner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If 3D information is generated and used to organize and display images, then the user interaction and immersion are enhanced, but the device complexity and processing requirements increase
Solution Approach 1:
The patent transitions from traditional 2D flat image layouts to 3D spatial arrangements by generating depth information from image pairs and using stereo visualization techniques. This dimensional change enables more immersive and interactive user experiences while organizing images in three-dimensional space based on captured location and orientation data.
Solution Approach 2:
The system performs preliminary 3D reconstruction and depth map generation during the image processing stage, creating pre-computed 3D representations that can be efficiently rendered and navigated later. This preliminary action reduces real-time processing requirements during user interaction.
2Measurement precision
If visual word frequencies are compared to identify related images, then image grouping accuracy is improved, but the processing time and computational resources increase
Solution Approach 1:
The patent divides the image analysis process into distinct stages: extracting visual words from images, computing frequency distributions, comparing histograms, and generating similarity scores. This segmentation allows for optimized processing at each stage and enables parallel computation of visual word frequencies across multiple images.
Solution Approach 2:
The system transforms image data into a different parameter space by converting visual features into visual word frequencies and histogram representations. This parameter transformation enables efficient comparison and matching by working with compressed frequency distributions rather than raw pixel data.
Data Source
AI summary
Techniques are provided for efficiently generating 3D information from a set of digital images. Techniques are also provided for displaying groups (or clusters) of digital images using 3D information associated with the digital images. In one technique, a group of digital images are displayed as a stack of thumbnail images where the thumbnail images are aligned on a display with respect to each other based on common features identified in the digital images, camera position, and/or camera pose. In another technique, a group of digital images are organized on a display in either a 3D layout or a 2D layout based on 3D information associated with each digital image in the group. In another technique, a transition effect is generated based on projections of two digital images onto a common scene plane and blending (or cross fading) one of the 3D projections with the other of the 3D projections.