Selective Image Data Acquisition Using Depth Map Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image processing systems face challenges in efficiently obtaining and processing image data of specific objects within a scene, particularly in bandwidth-constrained environments, where obtaining all image data is bandwidth-intensive and computationally demanding, and often requires unnecessary processing of the entire scene.
Innovation Solution
A method using a range sensor and an image sensor with a known spatial relation to capture depth information and visible light information, respectively, to identify a region of interest containing the object, allowing for selective acquisition of image data, reducing bandwidth and computational requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all image data from the entire scene is obtained and processed, then complete scene analysis is achieved, but bandwidth consumption increases and processing becomes computationally intensive
Solution Approach 1:
The patent segments the scene into multiple regions based on depth information from the range sensor. By dividing the full scene into discrete depth-based regions, the system can selectively process only those regions containing objects of interest, rather than analyzing the entire scene. This segmentation approach maintains measurement precision for relevant objects while significantly reducing the volume of image data that needs to be transmitted and processed.
Solution Approach 2:
The patent extracts only the necessary image data corresponding to specific regions of interest from the complete scene. Using depth map analysis, the system identifies and extracts image portions containing target objects, separating them from the rest of the scene. This extraction principle directly addresses the contradiction by obtaining precisely the data needed for analysis while leaving out unnecessary portions, thereby reducing bandwidth consumption without sacrificing analysis completeness.
2Quantity of substance
If all image data is obtained via a bandwidth constrained link, then complete image data is available for processing, but the bandwidth of the link is exceeded or significantly consumed
Solution Approach 1:
The patent performs preliminary analysis using depth map data before obtaining the actual image data. By first processing the compact depth information to identify regions of interest, the system determines in advance which image portions are necessary. This preliminary action enables selective data acquisition, ensuring that only the required quantity of image data is transmitted over the bandwidth-constrained link, thus avoiding bandwidth exhaustion while maintaining sufficient data availability for processing.
Solution Approach 2:
The patent introduces depth map data as an intermediary between the scene and the final image processing. The depth map serves as a mediator that guides the selection and transmission of image data. Instead of directly transmitting and processing all image data, the system uses the depth intermediary to filter and prioritize data transmission, reducing the total volume of data over the bandwidth-constrained link while ensuring adequate image data availability for the identified regions of interest.
3Measurement precision
If background removal processing is applied to all image data, then foreground objects can be extracted, but the processing becomes computationally intensive
Solution Approach 1:
The patent applies segmentation to the processing workflow by dividing the image data into multiple depth-based regions before performing background removal. Instead of applying computationally intensive background removal algorithms to the entire image, the system processes each segmented region separately. This segmentation approach maintains foreground extraction accuracy for objects in regions of interest while significantly reducing the total computational complexity by limiting processing to smaller, relevant portions of the image.
Solution Approach 2:
The patent extracts and processes only the image regions containing foreground objects, removing unnecessary background regions from the processing pipeline. By using depth information to identify and extract regions of interest before applying background removal algorithms, the system achieves accurate foreground extraction while minimizing computational complexity. The extraction principle ensures that processing power is concentrated on relevant data portions rather than being wasted on extensive background areas.
4Area of stationary object
If the field of view of the camera is used to determine the region of interest, then all visible areas are covered, but unnecessary areas are also processed
Solution Approach 1:
The patent introduces a depth dimension to the traditional two-dimensional field of view analysis. By incorporating depth information from the range sensor, the system creates a three-dimensional understanding of the scene that enables more precise region identification. This additional dimensional perspective allows the system to distinguish between foreground objects and background areas more effectively, covering the necessary field of view while excluding unnecessary regions from processing, thereby improving energy efficiency without sacrificing coverage.
Solution Approach 2:
The patent uses depth map data as an intermediary layer between the camera's field of view and the final region of interest determination. The depth map acts as a filtering mediator that processes the full field of view information and identifies which specific areas contain objects of interest. This intermediary approach enables the system to maintain comprehensive field of view coverage for monitoring purposes while using the depth mediator to eliminate unnecessary background areas from further processing, reducing energy consumption efficiently.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method and processor system are provided which analyze a depth map, which may be obtained from a range sensor capturing depth information of a scene, to identify where an object is located in the scene. Accordingly, a region of interest may be identified in the scene which includes the object, and image data may be selectively obtained of the region of interest, rather than of the entire scene containing the object. This image data may be acquired by an image sensor configured for capturing visible light information of the scene. By only selectively obtaining the image data within the region of interest, rather than all of the image data, improvements may be realized in the computational complexity of a possible further processing of the image data, the storage of the image data and/or the transmission of the image data.