3D Object Identification Using 2D Image Alignment
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Solution Overview
Problem
Manual methods for identifying the presence of 3D objects in construction sites are time-consuming and costly, requiring human intervention to compare design drawings with actual constructions, which can be improved through automated processes.
Innovation Solution
A method and apparatus that receive photographic images, calculate their positions and orientations, align them with a 3D model of the target object, generate inspection projection images, and determine similarity to automatically identify the presence of the 3D object using computer vision or deep learning methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to identify 3D objects in construction sites, then measurement precision can be achieved, but time consumption and cost increase significantly
Solution Approach 1:
The patent replaces manual mechanical inspection methods with an automated computer vision system. The system uses cameras to capture images, extracts feature points, and automatically compares them with 3D model data to identify object presence and measure dimensions, eliminating the need for manual measurement while maintaining precision.
Solution Approach 2:
The patent creates a digital copy of the construction site environment by capturing images and extracting feature points that represent the physical 3D space. This digital representation is then used for automated analysis and comparison with design models, allowing repeated inspections without manual intervention.
2Productivity
If automated image processing is used to identify 3D objects, then time and cost are reduced, but system complexity increases
Solution Approach 1:
The patent divides the complex inspection task into separate modular steps: image capture, feature point extraction, 3D model generation, and comparison analysis. Each step is handled by a dedicated module or algorithm, making the overall system more manageable and easier to implement while maintaining high automation.
Solution Approach 2:
The patent introduces feature points as intermediary elements that bridge the gap between 2D images and 3D models. These feature points serve as common references that enable automatic alignment and comparison, simplifying the complex task of registering multiple image sources with 3D design data.
3Reliability
If multiple photographic images are processed to ensure comprehensive coverage, then identification reliability improves, but processing time increases
Solution Approach 1:
The patent performs preliminary processing by extracting feature points and generating 3D models from images before the actual inspection comparison. This pre-processing creates ready-to-use data structures that accelerate the subsequent identification process, allowing multiple images to be processed efficiently without linear time increase.
Solution Approach 2:
The patent merges information from multiple photographic images by extracting common feature points and integrating them into a unified 3D representation. This consolidation allows the system to process multiple images simultaneously rather than sequentially, maintaining reliability while reducing total processing time.
Data Source
AI summary
Provided are a method and apparatus for identifying the presence of a 3D object using an image. According to the method and the apparatus, two-dimensional images are used to identify whether a 3D object exists in the images. According to the method and apparatus for identifying the presence of a 3D object by using an image, the presence of a 3D object in space can be accurately and quickly identified by using two-dimensional images, leading to higher productivity.