Integrated GUI for Visible-Light and LIDAR Object Identification
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Solution Overview
Problem
Legacy systems require users to manually identify and classify objects across independent images from visible-light cameras and LIDAR maps, leading to tedious and error-prone processes due to inconsistent perspectives and lack of intuitive interaction between the two data types.
Innovation Solution
A graphical user interface (GUI) is developed that integrates visible-light images and LIDAR maps, allowing users to interact with objects in one image to affect corresponding objects in the other, through features like highlighting, zooming, and rotating, thereby improving identification efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visible-light cameras and LIDAR systems are used separately to capture location data, then each technology provides its specific advantages (color/shape details from cameras, distance measurements from LIDAR), but the independent processing of these images requires manual identification and classification by users, which is tedious and error-prone
Solution Approach 1:
The patent combines visible-light camera images and LIDAR depth maps into a single integrated GUI display, allowing users to view both data types simultaneously in registered alignment. This merging eliminates the need to switch between separate images or manually correlate features, directly reducing identification time while maintaining accuracy through the complementary information provided by both sensing technologies.
Solution Approach 2:
The patent introduces an automated object identification system that acts as an intermediary between the raw sensor data and the user. This system automatically detects, classifies, and highlights objects in both the visible-light and LIDAR images, providing pre-processed information that guides user attention and reduces manual effort while maintaining high identification accuracy.
2Reliability
If users manually identify objects across independent images from different sensing technologies, then thorough classification may be achieved, but the process becomes tedious and error-prone due to inconsistent perspectives and lack of intuitive interaction
Solution Approach 1:
The patent merges multiple data types (visible-light images and LIDAR depth maps) into a single integrated display with consistent perspective and registration. This allows users to interact with one unified interface rather than switching between separate images, significantly improving ease of operation while maintaining classification reliability through the combined information from both sensing technologies.
Solution Approach 2:
The patent implements interactive feedback mechanisms where user actions in one image type (e.g., selecting an object in the visible-light image) automatically highlight corresponding features in the other image type (LIDAR depth map). This bidirectional feedback reinforces accurate identification, improves reliability by allowing cross-verification, and enhances ease of operation by providing intuitive visual cues that guide the classification process.
3Productivity
If separate processing of visible-light images and LIDAR maps is used, then each data type can be optimized independently, but the lack of integrated interaction between the two data types reduces overall identification efficiency
Solution Approach 1:
The patent merges the display and interaction of visible-light images and LIDAR maps into a single integrated GUI system, dramatically improving identification efficiency by allowing users to correlate features across both data types simultaneously. The system manages the complexity of integrating multiple sensing technologies through unified coordinate registration and synchronized rendering, presenting a simplified interface that handles the integration complexity internally while providing enhanced productivity to the user.
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
The integrated GUI reduces identification time and enhances accuracy by allowing seamless correlation and interaction between visible-light images and LIDAR maps, facilitating easier object identification and navigation for applications like autonomous vehicles.
Implementation Method 1
light detection and ranging (LIDAR)... LIDAR may include illuminating the location with one or more bursts of laser light, and then measuring the reflections of those bursts to identify distances between the capturing device and objects at the location
Data Source
AI summary
Embodiments may relate to a graphical user interface (GUI). The GUI may include a first portion that displays an image related to images of a location. The GUI may also include a second portion that displays an image related to detection and ranging information of the location. The two images may be linked such that an interaction with an object in one portion of the GUI causes changes in the other portion of the GUI. Other embodiments may be described or claimed.