sensorless-gaze-following-hri

name	sensorless-gaze-following-hri
description	Neuroscience-inspired framework for low-cost sensorless gaze following in Human-Robot Interaction. Uses computational models of human gaze perception to estimate where humans are looking without expensive eye-tracking hardware. Trigger words: sensorless gaze, gaze following, human-robot interaction, HRI, gaze estimation, neuroscience gaze, low-cost gaze tracking.

Sensorless Gaze Following for HRI

Overview

This skill implements a neuroscience-inspired framework for gaze following in Human-Robot Interaction (HRI) without requiring expensive eye-tracking hardware. By modeling human gaze perception mechanisms, robots can estimate where humans are looking using only standard cameras.

Core Principles

1. Head pose + scene context can predict gaze direction with surprising accuracy
2. Human gaze perception relies on integration of multiple visual cues
3. Neuroscience models of gaze processing can be computationally implemented

Implementation

import cv2
import numpy as np

class SensorlessGazeEstimator:
    def __init__(self):
        self.head_pose_model = self.load_head_pose_model()
        
    def estimate_gaze(self, frame, face_bbox):
        head_pose = self.head_pose_model.predict(frame, face_bbox)
        gaze_vector = self.compute_gaze_from_head_pose(head_pose)
        gaze_target = self.map_gaze_to_scene(gaze_vector, frame)
        return gaze_target
    
    def compute_gaze_from_head_pose(self, head_pose):
        eye_offset = self.neuroscience_gaze_model(head_pose)
        return head_pose + eye_offset

Applications

• Low-cost HRI systems
• Assistive robotics
• Social robots
• Behavioral analysis

Activation Keywords

sensorless gaze, gaze following, human-robot interaction, HRI, gaze estimation, neuroscience gaze, low-cost gaze tracking