Panorama Stitching for Region of Interest Localization in PTZ Cameras
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Solution Overview
Problem
Existing camera systems, particularly PTZ cameras, face challenges in accurately locating and updating regions of interest as they move unintentionally due to factors like wind gusts, and existing methods require access to camera orientation values or are computationally intensive and inaccurate.
Innovation Solution
A computer-based system generates a panorama by stitching images from multiple viewpoints and applies a transformation, such as homography, to maintain the location of regions of interest, even when the camera changes its viewpoint, using methods like Ransac, SIFT, or LoFTR, without relying on PTZ location values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If PTZ cameras are used to provide wide-area coverage with intentional panning, tilting, and zooming, then the coverage area and flexibility are improved, but the accuracy of locating regions of interest deteriorates due to unintentional camera movements
Solution Approach 1:
The patent creates a virtual copy of the scene through panorama stitching, combining multiple images from different viewpoints into a comprehensive panoramic view. This virtual copy maintains stable spatial relationships and allows accurate region of interest localization without being affected by camera movements, thus resolving the contradiction between wide coverage and location accuracy
Solution Approach 2:
The patent replaces reliance on mechanical camera orientation data (PTZ values) with a computational approach using image stitching and panorama generation. Instead of depending on mechanical system data that may be inaccurate or unavailable, the system uses image processing techniques to establish spatial relationships, thereby improving measurement precision independent of mechanical limitations
2Reliability
If existing methods are used to locate regions of interest in moving cameras, then the system can track objects, but the computational power requirements increase and accuracy decreases
Solution Approach 1:
The patent performs panorama stitching and region of interest localization in advance, creating a comprehensive spatial map before object tracking is needed. By pre-processing the images to establish coordinate transformations and identify regions of interest, the system reduces real-time computational requirements while maintaining tracking reliability
Solution Approach 2:
The patent introduces panorama coordinates and transformation matrices as intermediary representations between the captured images and the final object tracking results. This intermediary layer simplifies the computational process by providing a stable reference frame, reducing the complexity of direct tracking calculations and lowering energy consumption
3Speed
If camera orientation values are used to locate regions of interest, then the positioning can be updated in real-time, but the system becomes dependent on accurate PTZ data which may not be available
Solution Approach 1:
The patent extracts spatial information directly from image content through panorama stitching, removing the dependency on external PTZ orientation data. By deriving position and orientation information from the image sequences themselves, the system achieves real-time positioning updates while eliminating the complexity of PTZ data integration and validation
Data Source
AI summary
A system and method for locating a region of interest on an image captured by a camera including: in a preparation stage: stitching a plurality of images from multiple viewpoints of the camera into a panorama of surroundings of the camera, generating a mask indicative of the location of the region of interest in the panorama; and during runtime: generating a transformation between the panorama and the captured image; and applying the transformation to the mask to get the location of the region of interest in the captured image.