Multiresolution Image Representation for Real-Time Object Detection
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Solution Overview
Problem
The Viola-Jones method for object detection in digital images requires significant bandwidth for interconnecting bus due to the need for multiresolution representations, which hinders real-time object detection.
Innovation Solution
A method for real-time generation of a multiresolution representation of a digital image using a local memory to store and process image representations at successive resolutions, reducing the bandwidth required by loading parts of the current main representation into a local memory and calculating integral images, thereby constructing intermediate representations for object detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a multiresolution representation of the image is generated using the Viola-Jones method, then object detection capability is improved, but bandwidth consumption increases
Solution Approach 1:
The patent divides the multiresolution representation into main representations stored in main memory and intermediate representations stored in local memory. This segmentation allows the system to process only necessary portions of image data at high resolution while using lower resolution for other areas, thereby reducing overall bandwidth consumption while maintaining detection capability.
Solution Approach 2:
The patent applies different resolution qualities to different regions of the image based on their importance for object detection. Critical regions are processed with higher resolution stored in local memory, while less critical regions use lower resolution from main memory, optimizing the trade-off between detection accuracy and bandwidth usage.
2Speed
If the entire image is loaded into local memory for processing, then processing speed is improved, but memory bandwidth requirements increase
Solution Approach 1:
The patent extracts only the necessary portions of the image data from main memory to local memory for processing. Instead of loading the entire image, it selectively transfers relevant main representations and generates intermediate representations on-demand, reducing memory bandwidth requirements while maintaining processing speed for critical detection tasks.
Solution Approach 2:
The patent performs preliminary processing by generating main representations at multiple resolutions and storing them in main memory before actual object detection. This preliminary organization allows the system to quickly access and process only the necessary resolution levels during detection, improving processing speed without requiring full image loading into local memory.
Data Source
AI summary
A method and device for real-time generation of a multiresolution representation of a digital image for real-time generation are disclosed. A sequence of main representations of the digital image is stored at successive different main resolutions in a main memory. A part of a current main representation is loaded from the main memory into a local memory via a bus. A current main representation is processed by determining a corresponding part of an intermediate representation of the image having an intermediate resolution lying between the resolution of the current main representation and the resolution of the subsequent main representation. The loading and processing steps are repeated for other parts of the current main representation until all parts of the current main representation have been successively loaded and processed.