Optical Flow Frame Interpolation for Multi-Sensor Time Alignment
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Solution Overview
Problem
Camera frame synchronization in sensor systems, such as for autonomous or semi-autonomous vehicles, is challenging due to variations in exposure time, read out time, and frame rate differences among sensors, leading to asynchronous conditions that affect perception, prediction, and decision-making processes.
Innovation Solution
Implementing optical flow-based frame interpolation techniques using hardware accelerators like OFA to synchronize camera frames by detecting motion between frames and generating interpolated frames to align timestamps and reduce blur and incoherence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frame interpolation is performed to synchronize camera frames, then synchronization precision is improved, but processing time and computational load increase
Solution Approach 1:
The patent replaces general-purpose CPU/GPU processing with a dedicated optical flow accelerator (OFA) hardware unit. This specialized hardware performs optical flow calculations and frame interpolation operations much faster than general-purpose processors, reducing processing time while maintaining high synchronization precision. The OFA is specifically designed for optical flow computation, substituting complex mechanical/computational processes with optimized hardware circuits.
2Measurement precision
If frame interpolation is performed to synchronize camera frames, then synchronization precision is improved, but hardware resources are overburdened
Solution Approach 1:
The patent divides the frame interpolation task into separate functional modules: optical flow estimation, motion vector generation, and frame interpolation. The OFA hardware is segmented into specialized units that handle optical flow computation independently from other image processing tasks. This segmentation allows the system to allocate hardware resources more efficiently, processing synchronization tasks without overburdening the entire hardware system.
Solution Approach 2:
The optical flow accelerator (OFA) acts as an intermediary component between the camera sensors and the final synchronized frame output. It receives raw frames from multiple cameras, performs optical flow-based interpolation to synchronize them, and outputs synchronized frames to downstream processing stages. This intermediary hardware unit offloads the complex synchronization computation from the main CPU/GPU, protecting other system resources while achieving high precision synchronization.
3Productivity
If optical flow-based frame interpolation is used to increase frame rate, then frame rate consistency is improved, but processing complexity increases
Solution Approach 1:
The patent uses dedicated OFA hardware circuits to perform optical flow calculations and frame interpolation operations that would otherwise require complex software algorithms running on general-purpose processors. The hardware implementation of optical flow algorithms significantly reduces processing complexity while enabling consistent frame rate increases, as the OFA can process multiple frames concurrently with fixed, predictable latency.
Data Source
AI summary
In various examples, systems and methods are disclosed that perform motion detection across image frames, such as optical flow determination, to synchronize an asynchronous frame with respect to a target time for the asynchronous frame. For example, image frames from a sensor can be processed by an optical flow accelerator to detect displacement across the image frames, and the displacement can be used to interpolate a modified frame at the target time. This can be used to perform data collection and combining operations such as stitching and/or reconstruction. The synchronization can be performed from sensor data from sensors such as cameras, LIDAR sensors, and/or RADAR sensors.