Object Detection in Constrained Digital Devices via Motion-Triggered Classification
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Solution Overview
Problem
Current systems for scene interpretation and object detection in digital devices are complex, costly, and power-intensive due to the need for continuous operation and integration of multiple components for image analysis, which can be inefficient in terms of processing and power consumption.
Innovation Solution
A digital electronic device with a constrained processing unit and memory that reduces image resolution to identify hot pixels and regions of interest, allowing for object classification and scene analysis using machine learning methods, even with limited resources, and enables communication with external devices for further processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous operational mode is maintained for image analysis, then object detection capability is improved, but power consumption increases
Solution Approach 1:
The system employs motion sensors (PIR, microphones, microwaves) to detect changes in the monitored area and triggers image capture only when motion is detected. This periodic action based on event detection allows the system to maintain object detection capability while avoiding continuous operation, thereby reducing power consumption significantly.
Solution Approach 2:
The system uses passive infrared sensors and other detection means to automatically wake up the video camera when needed. This self-service mechanism eliminates the need for continuous monitoring by the main system, allowing it to remain in a low-power state while still maintaining the ability to detect and respond to objects of interest.
2Measurement precision
If complex systems with multiple components are integrated for image analysis, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The system divides the detection task into multiple stages: first, simple motion sensors perform initial detection to identify regions of interest; then, the video camera captures images only of these specific regions. This segmentation allows the system to achieve high detection accuracy without requiring all components to operate continuously, thereby reducing overall system complexity.
Solution Approach 2:
The patent introduces an intermediary processing step where motion detection results are used to trigger and guide the image capture process. This intermediary mechanism coordinates between the simple sensors and the complex image analysis system, allowing accurate detection while managing system complexity through controlled interaction between components.
3Measurement precision
If high-resolution images are processed for object classification, then classification accuracy is improved, but processing time increases
Solution Approach 1:
The system applies partial action by processing only the regions of interest identified by motion sensors rather than analyzing entire high-resolution images. This approach maintains classification accuracy for relevant objects while significantly reducing processing time by excluding irrelevant areas from computation.
Solution Approach 2:
The system performs preliminary motion detection and region identification before conducting detailed object classification. This preliminary action prepares the data in advance by identifying which regions require detailed analysis, allowing the subsequent classification process to focus computational resources on relevant areas and reduce overall processing time.
Data Source
AI summary
The present invention discloses a method operable on a digital electronic device comprising constrained processing unit employing a limited computer-readable storage medium, also known as a digital memory, for allowing an object classification process to be executed on an image. The object classification process may be allowed by a processing unit interlocking with a digital memory unit, which receives an image representing a digital image captured by light incident on an image sensor, denoted herein as an original image. In some cases, a computerized process operable on the digital processing may identify a list of pixel arrays located at the original image, and thereby allow a classification process to be operated on these pixel arrays. In some cases, a process operable on the digital processing may grant access to another computerized process to perform the classification process. In some cases, such a computerized process may be operated by a computerized device designed to communicate with the digital electronic device, and/or the components thereof.