Quadtree Compression for Bandwidth-Limited Object Tracking
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Solution Overview
Problem
Current systems face challenges in optimizing the rate-distortion trade-off for intensity-event modalities in multi-modal imaging frameworks, particularly in high-resolution imaging sensors like RGB and event sensors, where data bandwidth is limited, and existing compression techniques do not effectively address the joint optimization of object detection and tracking across these modalities.
Innovation Solution
A host-chip architecture is developed that employs a quadtree-based compression scheme, dynamic Viterbi optimization, and Poisson disk sampling to minimize weighted rate distortion, allowing for efficient transmission and processing of intensity and event data, and uses a fusion framework for object detection and tracking, enhancing the quality of distorted images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional compression techniques are used for intensity and event data, then implementation is simple, but rate-distortion optimization is insufficient and object detection/tracking performance deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the image into multiple blocks and processing each block independently through quadtree decomposition. This allows different compression strategies to be applied to different regions, optimizing rate-distortion tradeoff for each block while maintaining overall system performance.
Solution Approach 2:
The patent implements dynamic compression where the compression parameters are adaptively adjusted based on the content of each block. The system dynamically selects between different compression modes (skip, coarse, fine) for different blocks, enabling optimal rate-distortion performance without requiring complex global optimization.
2Measurement precision
If high-resolution data from both intensity and event sensors is transmitted, then object detection accuracy is improved, but data bandwidth consumption increases
Solution Approach 1:
The patent extracts only the essential information needed for object detection from the full-resolution intensity and event data. By identifying and transmitting only the relevant blocks that contain object information, the system significantly reduces bandwidth consumption while maintaining detection accuracy.
Solution Approach 2:
The patent applies different compression qualities to different regions of the image based on their importance. Regions containing objects of interest are transmitted with higher quality, while background regions use coarser compression, optimizing the tradeoff between bandwidth usage and detection performance.
3Measurement precision
If quadtree decomposition is applied to both intensity and event data, then rate-distortion optimization is improved, but computational complexity increases
Solution Approach 1:
The patent applies partial quadtree decomposition, where not all blocks require full decomposition. The system performs decomposition only to the extent necessary to achieve the desired compression ratio and quality, avoiding unnecessary computational overhead from excessive decomposition.
Solution Approach 2:
The patent performs preliminary analysis of the image content before applying quadtree decomposition. By pre-identifying regions of interest and predicting which blocks will benefit from decomposition, the system reduces computational complexity by avoiding decomposition of blocks that would not contribute significantly to rate-distortion optimization.
4Productivity
If bandwidth is limited, then transmission efficiency is improved, but data quality for tracking deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors tracking performance and adjusts compression parameters accordingly. When tracking accuracy begins to deteriorate due to aggressive compression, the system adapts by allocating more bandwidth to critical regions, maintaining reliable tracking despite bandwidth constraints.
Solution Approach 2:
The patent dynamically changes compression parameters such as block size, decomposition depth, and quality levels based on bandwidth availability and tracking requirements. This allows the system to optimize transmission efficiency while maintaining minimum quality thresholds necessary for reliable object tracking.
Data Source
AI summary
A system to process imaging data includes an imaging system configured to capture image data and event data of a scene, compress the image data and the event data, and transmit the compressed image data and compressed event data to a host. The host is operatively coupled to the imaging system, and includes a processor configured to perform object detection on the compressed image data and the compressed event data to identify one or more objects. The processor is also configured to perform object tracking on the one or more objects. The processor is also configured to predict one or more regions of interest for subsequent data capture based on the object detection and the object tracking. The processor is further configured to provide the one or more regions of interest to the imaging system to control capture of additional image data and additional event data by the imaging system.