Image Cropping Using Depth Information for Real-Time Item Tracking
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Solution Overview
Problem
Existing systems for identifying and tracking items in images are computationally intensive and time-consuming, especially when dealing with multiple items, making them incompatible with real-time applications.
Innovation Solution
A system that uses a combination of cameras and 3D sensors to identify and track items on a platform by selecting the best cameras for image capture based on item pose, reducing the number of images processed and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all cameras are used to capture images of multiple items, then item identification accuracy is improved, but processing time and computational load increase significantly
Solution Approach 1:
The patent segments the image processing task by dividing it into two stages: first, a 3D sensor captures depth information to identify item locations and poses; second, only selected cameras capturing views of specific items are used for detailed image processing. This segmentation reduces the total number of images processed while maintaining identification accuracy.
Solution Approach 2:
The system performs preliminary action by using the 3D sensor to pre-identify item locations, boundaries, and poses before selecting which camera images to process. This preliminary depth-based analysis allows the system to focus computational resources only on relevant images, reducing processing time while maintaining accuracy.
2Reliability
If multiple cameras capture images of all items, then complete item coverage is achieved, but hardware resource utilization decreases
Solution Approach 1:
The patent applies local quality by assigning different functions to different sensors: the 3D sensor handles depth mapping and item localization, while selected 2D cameras handle detailed visual identification. This specialized division allows each component to operate at optimal efficiency, improving overall hardware utilization.
Solution Approach 2:
The 3D sensor acts as an intermediary between the physical items and the 2D camera system. It provides depth information that mediates the selection process, determining which camera images are necessary for complete item tracking, thereby optimizing hardware resource usage.
3Measurement precision
If user scanning or manual identification is required, then item identification accuracy is maintained, but system throughput and scalability are reduced
Solution Approach 1:
The system implements self-service by automatically performing item identification and tracking without requiring user scanning or manual input. The combination of 3D sensing and selective 2D imaging enables the system to autonomously identify items, determine their poses, and track them throughout the space, significantly improving throughput and scalability.
Solution Approach 2:
The patent replaces the mechanical action of manual scanning with an automated sensor-based system. The 3D sensor and camera system automatically capture and process item information, substituting human physical interaction with automated optical and depth sensing mechanisms.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enables rapid identification and tracking of multiple items without requiring user intervention, improving hardware utilization and scaling capabilities.
Implementation Method 1
capture a depth image of items on the platform using a 3D sensor
Data Source
AI summary
A device configured to receive a first image of an item on a platform using a camera and to determine a first number of pixels in the first image that corresponds with the item. The device is further configured to receive a first depth image of an item on the platform using a three-dimensional (3D) sensor and to determine a second number of pixels within the first depth image that corresponds with the item. The device is further configured to determine that the difference between the first number of pixels in the first image and the second number of pixels in the first depth image is less than the difference threshold value, to extract the plurality of pixels corresponding with the item in the first image from the first image to generate a second image, and to output the second image.