Object Detection Area Limiting via Sensor Fusion

The patent divides the image into multiple regions based on sensor information (rotation angle, position data) and processes each region separately. This segmentation allows the system to focus computational resources only on areas where objects are likely to appear, rather than processing the entire image, thus reducing detection time while maintaining accuracy.

The patent applies different processing strategies to different regions of the image based on local characteristics determined by sensor data. High-priority regions (where objects are more likely to appear based on rotation and position) receive full detection processing, while other regions receive reduced or no processing, optimizing the balance between detection accuracy and processing time.

The patent extracts and utilizes sensor information (rotation detection sensor data, position sensor data) to identify and extract only the relevant regions from high-resolution images that contain potential objects. By taking out and processing only these extracted regions rather than the entire high-resolution image, the system maintains detection accuracy while significantly reducing computational load for real-time processing in mobile environments.

The patent performs partial action by processing only the necessary portions of the image (regions identified through sensor fusion) rather than the complete image. This partial processing approach provides sufficient detection accuracy for practical applications while reducing computation time to enable real-time performance on mobile devices with limited processing power.