3D Vision IP Block Segmentation for Power Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current technologies face challenges in efficiently processing 3D vision data in real-time, particularly in mobile and embedded devices due to high power consumption and limited processing capabilities, making it impractical for applications like augmented reality and gesture recognition.
Innovation Solution
An IP block hardware/logic design is implemented on a semiconductor chip to perform specific vision processing calculations, reducing power consumption and memory requirements by preprocessing camera data directly, allowing for efficient execution of 3D vision algorithms like SLAM, Key Point Detection, and Feature Calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If traditional CPU/GPU is used for 3D vision processing, then processing capability is sufficient, but power consumption is high and battery life is shortened
Solution Approach 1:
The patent segments the vision processing system into multiple specialized IP blocks, each dedicated to specific processing tasks (e.g., depth processing, color processing, feature detection). This segmentation allows the system to activate only the necessary processing blocks for each application, reducing overall power consumption while maintaining sufficient processing capability for 3D vision tasks.
Solution Approach 2:
The patent implements local quality by creating specialized processing units with different characteristics optimized for specific tasks. For example, separate IP blocks are designed for different processing requirements (depth vs. color data), allowing each block to operate at optimal efficiency for its specific function, thereby reducing total power consumption compared to using a general-purpose CPU/GPU for all tasks.
2Ease of operation
If vision processing is done on mobile devices, then accessibility is improved, but processing capability and memory capacity are limited
Solution Approach 1:
The patent changes the architectural parameters of mobile devices by integrating specialized vision processing IP blocks directly into the device hardware. This fundamental parameter change transforms the processing capability from software-based (CPU/GPU) to hardware-based specialized units, enabling 3D vision processing on mobile devices despite their limited overall processing power and memory capacity.
3Productivity
If real-time 3D processing is implemented, then application responsiveness is improved, but power consumption increases
Solution Approach 1:
The patent applies preliminary action by implementing dedicated hardware IP blocks that are pre-configured for specific vision processing tasks. These blocks are designed and optimized in advance to perform their functions efficiently, enabling real-time 3D processing without the need for complex software algorithms that would consume excessive power during execution.
Data Source
AI summary
Described are methods, systems, and apparatuses for 3D vision processing using an IP block. A vision processing module comprises an integrated circuit that performs one or more 3D vision processing algorithms and a plurality of controllers that couple the integrated circuit to each of: a sensor device, a processor, a memory module, and a network interface. The vision processing module receives image data from the sensor device, the image data corresponding to one or more images captured by the sensor device. The vision processing module executes one or more of the 3D vision processing algorithms using at least a portion of the image data as input. The vision processing module transmits an output from execution of one or more of the 3D vision processing algorithms to at least one of: the processor, the memory module, or the network interface.