Programmable Image Sensor Sparse Capture for Low-Power Vision
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Solution Overview
Problem
Existing image sensors lack dynamic configurability, leading to inefficiencies in power consumption, frame rate, and resolution, as they are typically not programmable by host applications, resulting in suboptimal performance for applications like object tracking and augmented reality, due to the need to transmit and process full frames of pixel data even when only a subset is necessary.
Innovation Solution
An image sensor system with a dynamically programmable pixel cell array and controller, allowing for sparse capture modes and two-tier feedback systems, where the controller processes image frames and updates programming signals based on host processor feedback, enabling selective output of pixel data based on detected features and ambient conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If full frames of pixel data are transmitted and processed, then complete image information is available, but power consumption and bandwidth requirements increase
Solution Approach 1:
The patent extracts and transmits only the necessary subset of pixel data (e.g., regions of interest, sparse pixel patterns) rather than complete full frames. This extraction approach maintains essential image information for applications like object tracking while significantly reducing power consumption and bandwidth requirements by eliminating redundant data transmission.
Solution Approach 2:
The system performs partial action by transmitting only the required portion of pixel data needed for specific applications. Instead of processing and transmitting complete frames, the patent implements sparse capture modes that send minimal necessary data, reducing energy consumption while maintaining sufficient information for the intended application purposes.
2Loss of information
If full frames of pixel data are transmitted and processed, then complete image information is available, but bandwidth requirements increase
Solution Approach 1:
The patent extracts and transmits only the necessary subset of pixel data (e.g., regions of interest, sparse pixel patterns) rather than complete full frames. This extraction approach maintains essential image information for applications like object tracking while significantly reducing power consumption and bandwidth requirements by eliminating redundant data transmission.
Solution Approach 2:
The system performs partial action by transmitting only the required portion of pixel data needed for specific applications. Instead of processing and transmitting complete frames, the patent implements sparse capture modes that send minimal necessary data, reducing energy consumption while maintaining sufficient information for the intended application purposes.
3Device complexity
If image sensors are not dynamically programmable, then device complexity is reduced, but adaptability to different applications deteriorates
Solution Approach 1:
The patent implements dynamic programmability that allows the image sensor to adapt its configuration in real-time based on application requirements. The controller can dynamically adjust pixel cell activation patterns, sparsity levels, and capture modes without requiring complex reconfiguration of the entire sensor architecture, enabling versatile application adaptation while maintaining manageable device complexity.
Solution Approach 2:
The patent creates a universal image sensor platform that can serve multiple applications through programmable control. The same hardware infrastructure supports diverse use cases including object tracking, augmented reality, and general imaging by dynamically adjusting operational parameters, eliminating the need for application-specific sensor designs.
4Ease of manufacture
If standard image sensors are used, then manufacturing simplicity is maintained, but performance for specific applications like object tracking deteriorates
Solution Approach 1:
The patent implements dynamic programmability that allows the image sensor to adapt its configuration in real-time based on application requirements. The controller can dynamically adjust pixel cell activation patterns, sparsity levels, and capture modes without requiring complex reconfiguration of the entire sensor architecture, enabling versatile application adaptation while maintaining manageable device complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces power consumption and bandwidth requirements by transmitting only relevant pixel data at higher speeds and resolutions, improving system performance and efficiency in applications like object tracking and augmented reality.
Implementation Method 1
Each pixel cell may include a photodiode to sense light by converting photons into charge (e.g., electrons or holes)
Data Source
AI summary
In one example, an apparatus comprises a pixel cell array and a controller formed within a semiconductor package. The pixel cell array is configured to: generate, at a first time and based on first programming signals received from the controller, a first image frame; transmit the first image frame to a host processor; and transmit the first image frame or a second image frame to the controller, the second image frame being generated at the first time and having a different sparsity of pixels from the first image frame. The controller is configured to receive second programming signals from a host processor, the second programming signals being determined by the host processor based on the first image frame; update the first programming signals based on the second programming signals; and control the pixel cell array to generate a subsequent image frame based on the updated first programming signals.