Front-Image Item Identification for Faster Multi-Item Tracking
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Solution Overview
Problem
Identifying and tracking multiple items in real-time is computationally intensive and time-consuming, making it incompatible with real-time applications, and maintaining accuracy in dynamic environments is challenging due to shifts in camera, 3D sensor, and platform positions.
Innovation Solution
A system using cameras and 3D sensors to identify and track items, with dynamic recalibration of homography to maintain accuracy, and intelligent detection of triggering events and item placement, reducing the need for user interaction and optimizing processing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image processing methods are used to identify and track multiple items, then comprehensive item identification is achieved, but processing time increases and real-time performance is lost
Solution Approach 1:
The patent extracts and removes back images from the set of captured images before processing. By identifying and eliminating images where items are positioned on their backs (which provide minimal identification value), the system reduces the number of images requiring computational analysis while preserving all useful identification information from front-facing images.
Solution Approach 2:
The patent segments the image processing task into distinct stages: first capturing multiple images from different angles, then filtering to identify front-facing versus back-facing images, and finally processing only the useful front-facing images for item identification. This segmentation allows parallel processing and optimizes computational resource allocation.
2Measurement precision
If multiple cameras are used to capture images from different angles, then item identification accuracy improves, but hardware complexity and processing load increase
Solution Approach 1:
The patent extracts only the necessary information from multiple camera inputs by identifying and selecting only front-facing images for processing. Instead of processing all images from all cameras, the system filters out back-facing images and processes only those providing useful identification data, effectively reducing the complexity burden of having multiple cameras.
Solution Approach 2:
The patent implements dynamic image selection based on the orientation and positioning of items in each captured image. The system adaptively determines which images are useful (front-facing) and which are not (back-facing), allowing the processing pipeline to dynamically adjust its input based on real-time scene conditions rather than processing a fixed set of images.
3Reliability
If all captured images are processed for item identification, then identification completeness is maintained, but computational resources are wasted on back images
Solution Approach 1:
The patent extracts and removes back-facing images from the processing pipeline before computational analysis occurs. By identifying images where items are positioned on their backs and eliminating these from further processing, the system maintains complete identification of all items while avoiding unnecessary computational energy expenditure on images that cannot provide identification information.
Solution Approach 2:
The patent captures more images than strictly necessary (including back-facing images from multiple angles) but then processes only the essential subset (front-facing images). This partial processing approach ensures that all items are captured from useful angles while avoiding the excessive computational cost of analyzing every captured image, achieving the optimal balance between completeness and efficiency.
Data Source
AI summary
A plurality of images are captured of the first item and a plurality of cropped images are generated based on the first images. An item identifier is identified based on each cropped image, wherein each item identifier is associated with a numerical similarity value. Each cropped image is further tagged as a front image or a back image. A particular item identifier identified for a corresponding cropped image tagged as a front image is selected and associated with the first item. An indicator of the particular item identifier is displayed on a user interface device.