OPTICAL FLOW-BASED FRAME INTERPOLATION TO SYNCHRONIZE BETWEEN SENSORS

Smart overview of the Invention

Systems and methods are introduced for synchronizing image frames from various sensors using optical flow-based frame interpolation. This technique helps align asynchronous frames to a target time, allowing for effective data collection and operations such as stitching and reconstruction. The system can process data from cameras, LIDAR, and RADAR sensors to achieve synchronization, crucial for applications in autonomous or semi-autonomous vehicles.

Technical Background

Synchronizing frames in sensor systems is essential for accurate perception and decision-making in autonomous vehicles. Variations in exposure and readout times, along with differing frame rates among sensors, pose challenges. The described method uses motion-based image processing to address these issues, improving the coherence of environmental representations for safe navigation.

Implementation Details

The system uses optical flow-based techniques to generate interpolated frames, aligning data streams from different cameras. An optical flow accelerator enhances hardware utilization, enabling applications like data collection, 3D reconstruction, and perception fusion. The process involves detecting asynchronous conditions in sensor data and generating frames based on detected motion, ensuring synchronization across sensors.

System Components

The described system includes processing units and memory units that execute operations for detecting asynchronous conditions and generating synchronized frames. These units detect motion through optical flow between frames and handle discrepancies in timestamps, including missing frames. The system is adaptable to various sensors, such as cameras, LIDAR, and RADAR, providing flexibility in different environments.

Applications and Use Cases

While the focus is on autonomous vehicles, the synchronization method is applicable to a wide range of technologies, including robotics, augmented reality, and surveillance. Synchronization can be achieved through hardware or software, ensuring accurate data collection timing and spatial alignment. This versatility makes the system valuable in diverse fields requiring precise sensor data integration.