Lidar Object Recognition Apparatus for Closely Located Objects
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Solution Overview
Problem
Conventional laser radar systems inaccurately recognize multiple objects closely located along the scan direction as a single object, leading to erroneous vehicle detection and behavior analysis.
Innovation Solution
An object recognition apparatus that uses a combination of lidar and imaging units to detect candidate areas with adjacent objects, divides these areas into individual object regions based on measured-distance data, and performs image recognition to accurately identify and track each object, preventing erroneous recognition of multiple objects as a single entity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If laser beams are emitted sequentially along a predetermined scan direction to detect objects, then the system can cover a wide detection area, but multiple objects closely located along the scan direction are erroneously recognized as a single object
Solution Approach 1:
The patent divides the detection area into multiple scan regions along the scan direction. By segmenting the continuous laser beam path into discrete scan regions, the system can independently process and identify objects in each region, preventing closely located objects from being merged into a single detection result.
Solution Approach 2:
The patent introduces an additional dimension of analysis by considering the scan direction as a separate spatial dimension. Objects are identified not only by their position perpendicular to the scan direction but also by their position along the scan direction, enabling the system to distinguish between objects that are close together along the scanning path.
2Area of stationary object
If the laser beam width is increased to improve detection coverage, then more objects can be detected simultaneously, but the precision of locating individual objects decreases
Solution Approach 1:
The patent segments the wide laser beam detection into multiple narrow scan regions. Each scan region is processed independently to identify objects with high precision, while the collection of all scan regions provides comprehensive coverage. This segmentation allows the system to maintain both wide coverage and high precision simultaneously.
Solution Approach 2:
The patent applies different processing qualities to different parts of the detection area. In regions where objects are closely located, the system uses higher precision processing with narrower effective beam width, while in regions with sparse objects, it uses broader detection. This local quality adjustment optimizes both coverage and precision in different spatial contexts.
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
Enhances the accuracy of recognizing multiple objects along the scan direction, allowing for precise detection and tracking of individual objects, reducing processing time and preventing erroneous recognition.
Implementation Method 1
a laser radar system... generates a measured-distance datum every time a laser beam is emitted, based on a reflected wave from an object
Implementation Method 2
the present invention relates to a method and apparatus for recognizing presence of objects from the detection results obtained from a laser radar system
Data Source
AI summary
An object recognition apparatus is provided, which enhances accuracy in recognizing more than one object to be detected closely located along a scan direction. In the apparatus, measured-distance datums included in an area formed by those measured-distance datums which are spaced apart by a distance of not more than a predetermined allowable value are grouped as one candidate area. The candidate area, if it has a size larger than a specified value, is regarded as a special candidate area. An object area on an image datum corresponding to the special candidate area is subjected to an image recognition process to define the range of the objects residing therein. The special candidate area is divided at a border between the objects based on the defined range. All candidate areas including the divided new candidate areas are subjected to a tracing process to confirm an object in each candidate area.