Remote Sensing Device Control via Facial Gaze Analysis
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Solution Overview
Problem
In settings with multiple organisms, such as sports events or security-monitored areas, there is often a delay in camera operators noticing noteworthy activities, leading to incomplete capture or monitoring of events.
Innovation Solution
Facial information from organisms is used to determine collective gaze direction, generating a signal to orient remote sensing devices like cameras automatically to capture activities in the focused direction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If camera operators manually monitor venues, then they can capture noteworthy activities, but there is a significant delay in noticing and responding to events
Solution Approach 1:
The system enables self-service by allowing the venue environment itself to direct camera attention. Facial information from spectators automatically indicates noteworthy activities, eliminating the need for manual operator intervention. The cameras serve themselves by receiving directional signals based on collective gaze patterns.
Solution Approach 2:
The system implements feedback by using facial information from spectators as input to automatically adjust camera directions. The collective gaze data provides real-time feedback about noteworthy activities, creating a closed-loop system where camera operators receive immediate directional guidance without manual intervention.
2Reliability
If cameras are focused on specific portions of the venue, then those areas are monitored, but other noteworthy activities go unmonitored
Solution Approach 1:
The system achieves universality by using a single facial information analysis mechanism to control multiple cameras across different venue portions. The same facial detection and gaze analysis technology serves all camera directions, providing comprehensive coverage without requiring separate control systems for each camera.
Solution Approach 2:
The system transitions from one-dimensional manual camera control to multi-dimensional automated control by incorporating facial information spatial distribution. Instead of controlling cameras based on operator perspective alone, the system adds the dimension of spectator gaze direction to determine camera positioning, enabling comprehensive venue coverage.
3Loss of information
If multiple cameras monitor different venue portions, then coverage is comprehensive, but it becomes difficult to know which portions require attention
Solution Approach 1:
The system introduces facial information as an intermediary that bridges the gap between comprehensive camera coverage and intelligent direction selection. Spectator facial data serves as the mediator that translates venue activity into actionable camera direction signals, eliminating the need for operators to manually determine which areas need attention.
Solution Approach 2:
The system replaces the mechanical system of manual camera operation with an automated information processing system. Instead of operators physically controlling cameras based on visual monitoring, facial information detection and analysis automatically determines camera directions, substituting human mechanical control with automated computational control.
Data Source
AI summary
Embodiments for controlling a remote sensing device by one or more processors are described. Facial information associated with a plurality of organisms is received. A remote sensing direction for a remote sensing device is selected based on the received facial information. A signal representative of the remote sensing direction is generated.