Depth Map Floor Wall Ceiling Identification IR Illuminator Lookup Tables
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Solution Overview
Problem
Current video surveillance systems face challenges in efficiently utilizing infrared emitters to provide accurate depth maps and object classification, leading to increased false alerts and inefficient motion detection, particularly in environments with varying lighting conditions and multiple movement sources.
Innovation Solution
The system generates lookup tables based on simulated IR light intensities from a camera's IR illuminators to estimate spatial depth and classify objects, using these tables to create depth maps and identify specific features like windows, floors, and ceilings, thereby improving alert accuracy and reducing false positives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional motion detection algorithms are used in video surveillance systems, then the system can detect movement in the scene, but it generates many false alerts and cannot differentiate between relevant and irrelevant movements
Solution Approach 1:
The patent introduces depth as a new dimension by using infrared illuminators at multiple positions to create depth maps. This transforms traditional 2D motion detection into 3D spatial awareness, allowing the system to distinguish between movements at different distances from the camera. Objects at varying depths create unique illumination patterns that enable more accurate classification of motion relevance, reducing false alerts while maintaining detection sensitivity.
Solution Approach 2:
The patent uses infrared illuminators as intermediary elements to probe the scene and generate depth information. These illuminators act as mediators between the camera and the monitored environment, casting infrared light that reflects off objects at different distances. The resulting illumination patterns serve as intermediaries for deriving depth maps, which then enable more sophisticated motion analysis and false alert reduction.
2Measurement precision
If infrared emitters are used to illuminate the scene for depth determination, then depth maps can be generated, but the system complexity increases due to multiple illuminator configurations
Solution Approach 1:
The patent segments the infrared illumination function across multiple spatially distributed illuminators rather than using a single complex light source. Each illuminator is positioned at a known location relative to the camera sensor, and their individual contributions are separately captured and processed. This segmentation simplifies the overall system design by using multiple simple, identical components instead of one complex illumination system, while still achieving accurate depth measurement through the combined information.
Solution Approach 2:
The patent changes the spatial parameter of the infrared illuminators by positioning them at multiple known locations relative to the camera sensor. This parameter change from a single illumination point to multiple illumination points enables depth determination through triangulation and pattern analysis. The known positional parameters of each illuminator are used in conjunction with the captured illumination patterns to calculate depth information, transforming a complex measurement problem into a solvable geometric relationship.
3Measurement precision
If lookup tables are generated for each pixel and depth combination, then depth estimation accuracy is improved, but the memory requirements and processing time increase significantly
Solution Approach 1:
The patent performs preliminary action by pre-generating lookup tables during a calibration phase before actual surveillance operation. The lookup tables, which contain expected illumination patterns for various depth values and illuminator configurations, are computed in advance and stored in memory. During real-time operation, the system only needs to perform simple table lookups and comparisons rather than complex calculations, dramatically reducing processing time while maintaining high depth estimation accuracy.
Solution Approach 2:
The patent uses copying by creating simplified representative models of illumination patterns for different depth scenarios. Instead of performing complex physical simulations or calculations in real-time, the system creates lookup tables that copy the essential characteristics of expected illumination patterns under various conditions. These copied patterns enable rapid matching and depth determination during surveillance operation without requiring repeated complex computations.
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
This approach enhances the accuracy of depth estimation and object classification, reduces false alerts, and allows for more efficient motion detection by differentiating between relevant and irrelevant movements in complex surveillance environments.
Implementation Method 1
video surveillance systems face challenges in efficiently utilizing infrared emitters to provide accurate depth maps and object classification
Implementation Method 2
The camera system has a 2-dimensional array of image sensors (e.g., photodiodes) and a plurality of IR illuminators
Data Source
AI summary
A process identifies large planar surfaces in scenes. The process receives captured IR images of a scene taken by a 2-dimensional array of image sensors of a camera system. Each IR image is captured when a distinct subset of IR illuminators of the camera system is illuminated. The process constructs a depth map of a scene using IR images and uses the depth map to compute a binary depth edge map for the scene. The binary depth edge map identifies which points in the depth map comprise depth discontinuities. The process identifies contiguous components based on the binary depth edge map and determines that a first component of the contiguous components represents a large planar surface in the scene by: fitting a plane to points in the first component; determining the orientation of the plane; and determining that the plane fitting residual error is less than a predefined threshold.