Dynamic Privacy Mask for Video Camera Field of View
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Solution Overview
Problem
Existing video surveillance camera systems with adjustable fields of view face challenges in maintaining effective privacy masking as the camera's field of view changes, as current systems fail to accurately transform privacy masks to cover the same subject matter across different camera orientations and zoom levels.
Innovation Solution
A surveillance camera system with a processing device that allows users to define privacy masks by vertices or pixel blocks, which are then transformed based on changes in the camera's field of view, ensuring the mask obscures substantially common subject matter across various camera orientations and zoom levels, including the ability to create donut-shaped masks with unmasked areas entirely surrounded by masked areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed privacy mask is used in a camera system with adjustable field of view, then the mask definition is simple, but the mask cannot accurately cover the same subject matter when camera orientation or zoom changes
Solution Approach 1:
The privacy mask is transformed dynamically according to camera movements. The system calculates transformed mask coordinates based on camera pan, tilt, and zoom parameters, allowing the mask to adapt its position and shape in real-time to maintain accurate coverage of private areas despite changes in field of view.
Solution Approach 2:
The mask definition parameters (coordinates, shape, size) are changed according to camera state. When camera orientation or zoom level changes, the system recalculates mask parameters to maintain proper alignment with the private areas being obscured, ensuring consistent privacy protection across different viewing conditions.
2Reliability
If privacy masking is applied to all video images, then privacy protection is comprehensive, but automated tracking and video content analysis are interfered with
Solution Approach 1:
Different regions of the video image are treated differently. The privacy mask applies obscuration only to specific identified private areas (such as residences or private property), while leaving other regions of the image unmasked and available for automated tracking and content analysis functions.
Solution Approach 2:
The video image is segmented into masked and unmasked regions. The system identifies private areas that require obscuration and separates them from public or monitoring areas, allowing simultaneous operation of privacy protection and automated surveillance functions on different portions of the same image.
Data Source
AI summary
A system including a camera, display screen and processing device. A privacy mask obscures a portion of the displayed images. The processing device transforms the privacy mask in accordance with changes in the field of view of the camera, wherein, in a first field of view, the privacy mask is defined by a plurality of vertices having coordinates (x1, y1), . . . (xn, yn), and, in a second field of view, the processing device determines transformed coordinates, (x1′, y1′), . . . (xn′, yn′), for each of the vertices based upon changes in the field of view of the camera. The privacy mask is definable by pixel rows and the processing device identifies opposing ends of a plurality of the pixel rows, each of the identified ends defining one vertex of the privacy mask. The privacy mask may also include an unmasked area completely encircled by masked area.