Surrounding Intelligent Motion Sensor Threat Detection

The patent replaces radar-based detection with an optical camera system. The camera captures visual images of approaching threats, and image processing algorithms analyze these images to detect human figures and determine their approach velocity. This optical substitution enables detection at much greater distances (500+ feet) compared to radar systems, providing significantly more warning time for users to take evasive action.

The patent applies local quality by using human recognition algorithms that specifically analyze localized features within the captured images. The system looks for human-specific characteristics such as body shape, head position, and gait patterns in the detected objects. This selective analysis of specific image regions and features enables the system to distinguish between human threats and non-threatening objects like birds, significantly reducing false alarms while maintaining high reliability in threat detection.

The patent applies preliminary action by implementing a multi-stage processing pipeline. First, the system performs initial detection to identify potential objects in the scene. Then, it pre-processes these detected objects by extracting key features and filtering out obvious non-threats before applying the full human recognition algorithm. This staged approach performs computationally intensive image processing only on relevant regions and objects, significantly reducing overall processing complexity while maintaining high detection accuracy for actual threats.