Privacy Protection

During the exploration of data protection policies, I utilized the latest release from Ultralytics: YOLOv11. Compared to YOLOv8, YOLOv11 is significantly faster and more accurate, making it an excellent choice for implementing privacy features like object blurring.

Benefits of Using YOLOv11 for Object Blurring

1. Privacy Protection: Effectively obscures sensitive or identifiable information, ensuring compliance with data protection policies like GDPR.

2. Selective Focus: Targets specific objects (e.g., faces) for blurring, while maintaining essential visual content for navigation and safety.

3. Real-Time Processing: Executes object blurring efficiently in dynamic environments, making it suitable for instant privacy enhancements.

Using YOLOv11, I trained and deployed a model on the Go2 robot. As shown in the GIF below, the robot can detect a person’s face, blur the region effectively, and display this blurred view on its screen. This functionality works as long as the person remains within the robot camera’s frame.

Facedetection and Faceblurring

YOLOv11 Performance Comparison

The chart below illustrates how YOLOv11 outperforms earlier models like YOLOv8 in terms of speed and accuracy. YOLOv11 introduces significant improvements, making it the preferred choice for real-time applications such as privacy-focused object detection and blurring.

Ultralytics Performance Reference

Key Observations

• Speed: YOLOv11 processes frames faster than YOLOv8, making it ideal for dynamic environments like retail stores where robots must respond quickly.

• Accuracy: YOLOv11 demonstrates higher detection accuracy compared to YOLOv8, ensuring reliable identification and processing of objects and faces.

• Efficiency in Privacy Tasks: With improved performance metrics, YOLOv11 ensures privacy protection features, such as object blurring, are executed without compromising system speed or functionality.

Using YOLOv11, I trained and deployed a model on the Go2 robot. The robot effectively detects a person’s face, blurs the region, and displays this securely on its screen while ensuring smooth operation.

Generalization Across Cameras

Note

While this application was tested with the Go2 robot, it is designed to work with other cameras as well, including the ZED 2i. This flexibility ensures the solution can be applied across different hardware configurations, enhancing its usability in diverse environments. For more details about YOLOv11, refer to the Ultralytics YOLO11 Documentation.