Smart Image Sensor with Local Processor for Latency Reduction
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Solution Overview
Problem
Current camera systems lack processing intelligence, leading to inefficient data flows, increased latency, and power consumption due to the need for extensive data movement between the camera and the computing system's general-purpose processing core, particularly evident in functions like auto-focus and image stabilization.
Innovation Solution
Integration of a smart image sensor with local memory and processor within the camera package, enabling on-camera processing and analysis of image data, reducing the need for large data transfers and allowing for real-time control of camera functions such as auto-focus and image stabilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If image data is transferred from camera to processing core through I/O control hub and memory controller, then the processing core can execute camera functions, but latency increases and power consumption increases
Solution Approach 1:
The patent segments the processing system into two parts: a processing core for complex functions and an integrated processor within the camera for preliminary processing. The integrated processor handles tasks like region of interest identification and image stabilization locally, while only essential data is transferred to the processing core, reducing latency and traffic congestion.
Solution Approach 2:
The patent adds a new dimension to the data flow architecture by introducing an integrated processor within the camera package that operates in parallel with the external processing core. This creates multiple processing paths, allowing simultaneous local processing and external processing, thereby reducing overall latency.
2Extent of automation
If entire frames of image data are directed through I/O control hub and memory controller to system memory, then auto-focus routine can be executed, but data movement increases power consumption
Solution Approach 1:
The patent extracts the essential processing function from the main data flow by implementing a dedicated integrated processor within the camera. This processor specifically handles auto-focus and other camera functions locally, extracting only the necessary processed information rather than transferring entire frames, thereby reducing power consumption associated with data movement.
Solution Approach 2:
The integrated processor within the camera performs self-service by autonomously executing camera functions such as auto-focus and image stabilization using locally stored program code. This eliminates the need for continuous data transfer to external processors, reducing power consumption while maintaining autonomous operational capability.
3Extent of automation
If feedback command progresses through memory controller and I/O control hub from processing core to camera, then processing results are communicated, but additional latency is observed
Solution Approach 1:
The integrated processor performs preliminary processing actions locally within the camera, including preliminary analysis and command execution. By handling feedback processing locally rather than waiting for external processor commands to traverse through multiple controllers, the system reduces feedback latency while maintaining automated processing capability.
4Device complexity
If camera has little or no processing intelligence, then device complexity is reduced, but traffic congestion increases in system data paths
Solution Approach 1:
The patent implements a dynamic architecture where the camera can operate in multiple modes: basic capture mode with minimal processing (low complexity) and enhanced processing mode using the integrated processor (higher complexity). This dynamic capability allows the system to adapt processing intelligence to task requirements, improving data transfer efficiency when needed while maintaining simplicity when not required.
Data Source
AI summary
An apparatus is described. The apparatus includes a smart image sensor having a memory and a processor that are locally integrated with an image sensor. The memory is to store first program code to be executed by the processor. The memory is coupled to the image sensor and the processor. The memory is to store second program code to be executed by the processor. The first program code is to cause the smart image sensor to perform an analysis on one or more images captured by the image sensor. The analysis identifies a region of interest within the one or more images with machine learning from previously captured images. The second program code is to cause the smart image sensor to change an image sensing and/or optical parameter in response to the analysis of the one or more images performed by the execution of the first program code.