Edge Camera Object Detection for Low-Power Barrier Control
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Solution Overview
Problem
Existing systems face challenges in performing object recognition in edge devices such as cameras using a minimum number of processing cycles and processing power, particularly in constrained environments like low-power cameras or edge processors.
Innovation Solution
The solution involves combining multiple image analysis results in real-time using optimized runtime environments within edge devices, employing neural network-based inferencing models to perform object recognition efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If object recognition is performed in edge devices using traditional methods, then processing accuracy can be maintained, but processing power consumption and processing cycles increase significantly
Solution Approach 1:
The patent segments the object recognition process into multiple stages: first identifying regions of interest through motion detection or depth sensing, then applying full image analysis only to those specific regions. This segmentation allows the system to maintain processing accuracy while significantly reducing the computational load and power consumption on edge devices.
Solution Approach 2:
The system performs partial action by applying computationally intensive object recognition algorithms only to selected regions of interest rather than entire frames. Motion-detected areas or depth-mapped regions are processed in detail, while the rest of the image receives minimal or no processing, thereby reducing processing cycles and energy consumption while maintaining detection accuracy.
2Measurement precision
If multiple sensors and processing units are added to improve object recognition capability, then detection accuracy improves, but device complexity increases
Solution Approach 1:
The patent merges multiple sensing modalities (motion detection, depth sensing, and image capture) into an integrated system where each sensor type complements the others. Motion detection identifies candidate regions, depth sensing provides spatial context, and image analysis confirms object identity. This merging approach improves detection accuracy while managing complexity through coordinated operation of unified sensor modules.
Solution Approach 2:
The system uses motion detection and depth sensing as intermediary processes that prepare and filter data before applying complex object recognition algorithms. These intermediary steps reduce the complexity of the final recognition task by pre-identifying regions of interest and providing contextual information, thereby improving accuracy without proportionally increasing overall system complexity.
3Loss of time
If real-time processing is implemented in edge devices, then response time is reduced, but processing power requirements increase
Solution Approach 1:
The system implements periodic action by continuously monitoring for motion events or depth changes, and only activating full object recognition processing when such events occur. This event-driven periodic processing maintains real-time responsiveness to important events while avoiding continuous high-power processing, thereby reducing overall power consumption while preserving fast response times for critical detections.
Data Source
AI summary
Human or object presence in or absence from a field-of-view of a camera can be achieved by analyzing camera data using a processor inside of or adjacent to the camera itself. In an example, a video signal processing system receives image data from one or more cameras and uses a processing circuit to determine whether a designated object is or is not present at a particular time, during a particular interval, or over a designated sequence of frames. In an example, the designated object can include one or more of a human being, a vehicle, or a parcel. In an example, results of the determination, such as including positive human or object identification, can be used as a trigger for operation of a barrier or access door.