Dynamic Image Generation Using Depth Histogram Analysis
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Solution Overview
Problem
Current methods for obtaining depth images do not effectively utilize this information to generate dynamic images, limiting the creation of immersive and interactive visual content.
Innovation Solution
A computer device with a dynamic image generating system that includes a camera for capturing depth images, processing modules to convert depth information into histograms, and algorithms to calculate average depth values and generate blurred images based on these values, creating a sequence of dynamic images that simulate depth perception.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If depth images are obtained using traditional methods (depth-sensing camera or image processing), then depth information can be acquired, but this depth information is not effectively utilized to generate dynamic images
Solution Approach 1:
The patent applies dynamics by transforming static depth information into dynamic visual output. The system processes depth images through a series of dynamic operations including histogram conversion, average depth calculation, and iterative blurred image generation. Each iteration refines the visual output based on depth data, creating a sequence of dynamic images that evolve over time rather than producing a single static result, thus effectively utilizing depth information for dynamic content creation.
2Adaptability or versatility
If depth images are used to generate dynamic images, then immersive and interactive visual content can be created, but the process complexity increases
Solution Approach 1:
The patent segments the complex image processing task into distinct modular steps: (1) obtaining depth images, (2) converting depth information to histograms, (3) calculating average depth values, (4) generating blurred images through iterative processing, and (5) assembling final dynamic images. This segmentation allows each component to be optimized independently and simplifies the overall system architecture while maintaining high visual quality and interactivity.
Solution Approach 2:
The patent introduces intermediary data structures and processing layers between the input depth image and the final dynamic output. Key intermediaries include depth histograms, average depth value maps, and intermediate blurred image sequences. These intermediaries simplify the transformation process by breaking down complex depth information into manageable representations that can be systematically processed and combined to generate the final dynamic images.
Data Source
AI summary
A method for generating dynamic images applied to a computer device includes obtaining a depth image of a static image. A preset region of the depth image is converted into a histogram and an average depth value D is calculated therefrom. A first depth value d1 and a second depth value d2 are determined from the histogram according to the average depth value D. M numbers of third depth values d3 are calculated according to the first depth value d1 and the second depth value d2. Once M number of blurred images are generated according to each M number of third depth values d3, the M number of blurred images are played back according to a magnitude of the third depth value d3 corresponding to each of the M number of blurred images.