DSP and GPU Image Synthesis for Automotive 3D Displays
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Solution Overview
Problem
Existing park-assist systems in automobiles rely on audible cues and lack efficient methods to seamlessly merge live video streams from multiple cameras into a 3D image that can be rotated for different viewpoints, limiting the driver's visual understanding of the surroundings.
Innovation Solution
The system partitions computation between a digital signal processor (DSP) for image processing and a graphics processing unit (GPU) for rendering, using optimized meta-data structures to communicate results and efficiently merge multiple camera feeds into a 3D image that can be rotated, allowing for improved visual representation of the car's environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If computation is performed entirely on the DSP for image processing, then image processing capability is improved, but rendering and 3D transformation capability deteriorates
Solution Approach 1:
The patent divides the computation task into two segments: the DSP handles image processing (merging camera feeds, correcting distortion), while the GPU handles rendering and 3D transformations. This segmentation allows each processor to specialize in its strengths, resolving the contradiction between image processing capability and rendering capability.
Solution Approach 2:
The patent introduces an intermediary data structure (metadata containing merged image data and transformation parameters) that bridges the DSP and GPU. This intermediary enables efficient communication and data transfer between the two processors, allowing the system to leverage both DSP's image processing strength and GPU's rendering strength without direct complex interaction between them.
2Manufacturing precision
If computation is performed entirely on the GPU for rendering, then rendering quality is improved, but image processing efficiency deteriorates
Solution Approach 1:
The patent segments the workload so that the DSP handles computationally intensive image processing tasks (merging multiple camera feeds, distortion correction) efficiently, while the GPU handles rendering tasks. This segmentation prevents the GPU from being burdened with heavy image processing, maintaining both image processing efficiency and rendering quality.
Solution Approach 2:
The DSP performs self-service by handling image processing independently before passing results to the GPU. This self-service approach allows the DSP to optimize image processing without interfering with the GPU's rendering pipeline, maintaining high efficiency in both stages.
3Loss of information
If multiple camera feeds are merged into a 3D image, then visual awareness is improved, but computational burden increases
Solution Approach 1:
The patent segments the complex task of merging multiple camera feeds into 3D images across two processors: the DSP handles the initial merging and preprocessing, while the GPU handles the 3D transformation and rendering. This segmentation distributes the computational burden, preventing any single processor from being overwhelmed.
Solution Approach 2:
The DSP performs preliminary action by merging and preprocessing camera feeds before passing them to the GPU. This preliminary processing reduces the complexity of data the GPU must handle, thereby reducing the overall computational burden while still achieving comprehensive visual awareness.
4Manufacturing precision
If high-quality 3D rendering is implemented, then visual representation is improved, but device complexity increases
Solution Approach 1:
The patent segments the system into two specialized components: the DSP for image processing and the GPU for rendering. This segmentation allows each component to be optimized independently for its specific function, achieving high visual representation quality without requiring a single overly complex processor.
Solution Approach 2:
The patent leverages the universal capabilities of modern DSP and GPU architectures, which can handle multiple types of computations. The DSP can handle image processing and the GPU can handle both rendering and 3D transformations, reducing the need for additional specialized hardware and thereby managing device complexity.
Data Source
AI summary
This patent application focuses on partitioning the computation to perform the image processing on the DSP, communicate the results to the GPU in an optimized manner, and use the GPU to render 3D information to the display. This invention solves the problem of seamlessly merging live streams from plural automotive cameras into a 3D display that can be rotated to see different view points. This purpose is achieved by partitioning the computation task between a digital signal processor (DSP) for image processing and a graphics processing unit (GPU) for rendering and display. This invention also includes meta data structures for communication of results from the DSP to the GPU.