Spatial Positioning Method Using Calibrated Image Adjustment
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Solution Overview
Problem
Current camera-based surveillance systems face inaccuracies in determining the spatial position of objects due to factors like occlusion, scale variation, and object deformation, especially when sub-meter precision is required, as they rely on bounding-box coordinates which can vary significantly based on the camera's angle and capture orientation.
Innovation Solution
A method that involves obtaining a candidate region associated with the object, projecting it into a calibrated image, adjusting it based on image elements, and determining the spatial position using the adjusted projected region, which can include bounding-boxes, sets of pixels, or edges, to improve accuracy by aligning with the object's position relative to the ground.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If bounding-box coordinates are used to determine object position, then the positioning method is simple and computationally efficient, but the positioning precision deteriorates significantly when sub-meter accuracy is required
Solution Approach 1:
The patent segments the object detection process into multiple stages: initial bounding-box detection, candidate region identification, and precise position determination. By dividing the task, the system maintains computational efficiency from bounding-box methods while achieving higher precision through subsequent refinement steps that analyze specific regions within the bounding box.
Solution Approach 2:
The patent performs preliminary bounding-box detection to narrow down the search area, then uses this preliminary information to guide more precise positioning calculations. The initial bounding-box provides a starting point that reduces the computational scope for subsequent high-precision positioning, thereby maintaining efficiency while improving accuracy.
2Ease of operation
If bounding-box based positioning is used, then the implementation is straightforward, but the position accuracy varies significantly depending on camera angle and object orientation
Solution Approach 1:
The patent applies local quality by focusing computational resources on specific regions within the bounding box that provide more reliable position information. Instead of treating the entire bounding box uniformly, the method identifies and analyzes particular areas (such as contact points with the ground or characteristic features) that yield consistent position data regardless of camera angle or object orientation.
Solution Approach 2:
The patent changes the parameters used for position determination based on detected object characteristics and camera conditions. Rather than relying solely on fixed bounding-box coordinates, the system adjusts positioning parameters according to object type, orientation, and viewing angle, thereby maintaining consistency across diverse scenarios while preserving implementation simplicity through automated parameter selection.
Data Source
AI summary
A method for determining a spatial position of an object using an image calibrated relative to a reference frame. The method comprises, after obtaining a candidate region associated with the object in the reference frame and projecting the candidate region into the calibrated image, adjusting the projected candidate region based on an image element associated with the object in the calibrated image, and determining a spatial position of the object using the adjusted projected candidate region.