Dual Processor 3D Camera Data Frame Routing
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Solution Overview
Problem
Legacy electronic devices equipped with 3D cameras face significant processing overload due to insufficient computational capability for handling 3D camera data, requiring high-performance GPUs and DSPs that are often lacking.
Innovation Solution
An electronic device is designed with a first processor to acquire and generate image data frames, and a second processor to receive these frames, check attribute information, and supply relevant data to applications, optimizing 3D data processing by distributing the workload and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If a single processor is used to handle all 3D camera data processing tasks, then device complexity is reduced, but processing capability becomes insufficient leading to significant processing overload
Solution Approach 1:
The patent divides the data processing system into multiple specialized processors: a first processor for acquiring image data from the camera and generating data frames, and a second processor for receiving data frames, checking attribute information, and supplying data to applications. This segmentation allows each processor to be optimized for specific tasks, increasing overall processing capability while managing complexity through functional specialization rather than requiring a single overpowered processor.
2Power
If high-performance GPU and DSP are installed to meet 3D camera processing requirements, then processing capability is improved, but device cost and complexity increase
Solution Approach 1:
The patent implements a universal data processing framework where the first and second processors can handle various types of 3D camera data (depth information, RGB data, skeleton data, facial expression data) through standardized data frame structures and attribute information checking. This multi-functional approach allows the system to process different data types efficiently without requiring separate specialized hardware for each data type, reducing overall device complexity while maintaining high computation capability.
3Productivity
If all data processing operations are performed sequentially by a single processor, then device complexity is minimized, but processing time increases due to sequential execution
Solution Approach 1:
The patent segments data processing operations into distinct phases handled by different processors: the first processor performs image data acquisition and data frame generation in parallel with the camera, while the second processor simultaneously checks attribute information and supplies data to applications. This segmentation enables parallel execution of processing tasks, significantly improving productivity and reducing processing latency compared to sequential single-processor execution.
4Measurement precision
If detailed attribute information checking is performed on all data frames, then data accuracy and applicability are improved, but processing overhead increases
Solution Approach 1:
The patent applies local quality by checking only the necessary attribute information in data frames based on specific processing requirements. The second processor checks attribute information selectively rather than processing all possible attributes uniformly, allowing the system to maintain high data accuracy for relevant attributes while reducing processing overhead for unnecessary attributes, thus balancing measurement precision with processing throughput.
Data Source
AI summary
An electronic device and data processing method thereof is provided. The electronic device of the present disclosure includes a first processor which acquires image data from a camera and generates a data frame based on the image data and a second processor which receives the data frame from the first processor, checks attribute information of the data frame, and supplies information on the data frame to at least one of a plurality of applications corresponding to the attribute information.