Mapping Range Sensor Data on Image Sensor Data
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Solution Overview
Problem
Existing mobile mapping systems (MMS) face challenges in accurately identifying and processing images of moving objects, particularly those relative to the fixed world, while also dealing with privacy-sensitive data such as faces and license plates, which are not effectively addressed by prior methods relying solely on image properties or short-time trajectory approximations.
Innovation Solution
A computer arrangement that receives time and position data, along with range sensor data from multiple sensors, to identify objects and calculate motion vectors, allowing for accurate mapping and processing of images by creating masks based on point clouds, enabling the removal of privacy-sensitive data and improving object detection and tracking in MMS images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image properties alone are used to identify moving objects, then the system complexity is low, but the detection precision and reliability are insufficient
Solution Approach 1:
The patent combines multiple data sources (image properties, range sensor data, position data, time data) into a unified object identification system. This integration allows the system to achieve high detection precision by cross-referencing multiple independent measurements, resolving the contradiction between simplicity and accuracy.
Solution Approach 2:
The patent introduces intermediate processing steps including mask creation from point clouds, motion vector calculation, and trajectory approximation. These intermediaries bridge the gap between raw sensor data and final object identification, enabling accurate detection of moving objects while maintaining systematic processing.
2Reliability
If multiple sensors are used to improve object detection accuracy, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent creates a multi-functional processing system where a single computer arrangement handles diverse sensor types (cameras, range sensors, position determination devices). The unified processing architecture performs multiple functions including data reception, point cloud generation, mask creation, motion analysis, and object identification, reducing operational complexity despite multiple sensors.
Solution Approach 2:
The patent segments the complex sensing system into distinct functional modules: data reception module, point cloud generation module, mask creation module, motion vector calculation module, and object identification module. This segmentation allows each component to be optimized independently while maintaining overall system reliability.
3Productivity
If short-time trajectory approximation is used for moving objects, then the processing speed is fast, but the position accuracy relative to fixed world is insufficient
Solution Approach 1:
The patent performs preliminary actions by creating masks from point clouds before final object identification, and by calculating motion vectors in advance. This preliminary processing of trajectory data allows the system to maintain high processing speed while incorporating accurate position information into the final object identification, resolving the speed-accuracy tradeoff.
Solution Approach 2:
The patent uses feedback mechanisms where detected object positions and motion vectors are continuously refined by comparing with range sensor data and position data. This feedback loop allows the system to maintain high processing speed while progressively improving absolute position accuracy through iterative refinement.
Data Source
AI summary
A method of and arrangement for mapping first range sensor data from a first range sensor to image data from a camera are disclosed. In at least one embodiment, the method includes: receiving time and position data from a position determination device on board a mobile system, as well as the first range sensor data from the first range sensor on board the mobile system and the image data from the camera on board the mobile system; identifying a first points cloud within the first range sensor data, relating to at least one object; producing a mask relating to the object based on the first points cloud; mapping the mask on object image data relating to the same object as present in the image data from the at least one camera; and performing a predetermined image processing technique on at least a portion of the object image data.