Stereo Camera Tracking for Water-Surface Objects
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Solution Overview
Problem
Existing tracking systems for marine vessels face challenges in maintaining accurate tracking of water-surface objects due to unpredictable changes in object movement and posture, leading to low tracking accuracy.
Innovation Solution
A tracking system utilizing a stereo camera with multiple imaging units on a marine vessel, where a processor acquires and processes images to detect objects, sets a tracking target based on temporal feature changes, and corrects tracking results using detected objects from multiple images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single imaging unit is used for tracking, then the device complexity is low, but the tracking accuracy deteriorates when object appearance changes due to movement or posture changes
Solution Approach 1:
The imaging system is divided into multiple independent imaging units (first imaging unit, second imaging unit, and additional imaging units). Each unit captures images from different viewpoints, allowing the system to track objects even when their appearance changes due to movement or posture changes. The processor integrates information from multiple segmented imaging sources to maintain accurate tracking.
Solution Approach 2:
The system transitions from single-viewpoint imaging to multi-viewpoint imaging by adding spatial dimensions. Multiple imaging units are positioned at different locations and orientations, capturing the object from multiple angles simultaneously. This dimensional expansion provides redundant information that improves tracking accuracy when the object's appearance changes.
2Measurement precision
If stereo camera with multiple imaging units is used, then the tracking accuracy improves through temporal feature changes, but the device complexity increases
Solution Approach 1:
The system performs preliminary object detection using the first and second images from the stereo camera before tracking. This preliminary detection establishes initial object parameters and features that are then used to guide subsequent tracking operations. By preparing detection results in advance, the system improves tracking accuracy while managing processing complexity efficiently.
Solution Approach 2:
The system uses detected objects from multiple images as feedback to correct tracking results. The processor continuously compares newly detected object features with previously tracked features and adjusts the tracking accordingly. This feedback mechanism maintains high tracking accuracy even when objects undergo significant appearance changes.
3Reliability
If traditional single-camera tracking is used, then the system is simple to operate, but the ability to predict movement and maintain accurate positioning deteriorates
Solution Approach 1:
The system merges multiple image sources (first imaging unit, second imaging unit, and additional imaging units) into a unified tracking system. The processor combines information from all imaging units to create a comprehensive view of the object's position and movement. This merging of multiple data sources improves tracking reliability by providing redundant information and better predicting object movement patterns.
Data Source
AI summary
A tracking system for tracking water-surface objects includes a stereo camera on a hull, at least one memory, and at least one processor coupled to the at least one memory. The at least one processor is configured or programmed to detect at least one object based on a first image and a second image captured by a first imaging unit and a second imaging unit of the stereo camera, and set one detected object as a tracking target in a third image captured by the first imaging unit, the second imaging unit or another imaging unit. The at least one processor is further configured or programmed to track the tracking target using a temporal change in a feature of the tracking target, and use at least one object detected based on the first image and the second image during tracking to correct the tracking result.