US 12,243,302 B2
Utilizing machine learning models to classify vehicle trajectories and collect road use data in real-time
Andrew Poole, Dublin (IE); Anthony Mccoy, Dublin (IE); Antonio Penta, Dublin (IE); and Phillip Lynch, Bettystown (IE)
Assigned to Accenture Global Solutions Limited, Dublin (IE)
Filed by Accenture Global Solutions Limited, Dublin (IE)
Filed on Oct. 25, 2022, as Appl. No. 17/972,940.
Prior Publication US 2024/0135705 A1, Apr. 25, 2024
Prior Publication US 2024/0233369 A9, Jul. 11, 2024
Int. Cl. G06V 20/10 (2022.01)
CPC G06V 20/182 (2022.01) 20 Claims
OG exemplary drawing
 
1. A method, comprising:
receiving, by a device, tracking data identifying trajectories of objects;
annotating, by the device, the tracking data to identify object categories for the tracking data;
utilizing, by the device, an object detection model to identify the objects based on the object categories;
processing, by the device, the objects, with a multi-object tracking model, to determine object trajectories for the objects;
utilizing, by the device, planar homography to transform the object trajectories to overhead planar trajectories;
processing, by the device, the overhead planar trajectories, with a noise reduction model, to generate simplified object trajectories;
converting, by the device, a continuous space associated with the simplified object trajectories into a discrete space;
utilizing, by the device, a Hilbert curve with the discrete space to convert the discrete space to a lower dimensional space;
utilizing, by the device, the lower dimensional space and the discrete space to transform the object trajectories to binary feature vectors;
processing, by the device, the binary feature vectors, with a clustering model, to determine trajectory clusters;
training, by the device, a classification model, with the binary feature vectors and the trajectory clusters, to generate a trained classification model; and
performing, by the device, one or more actions based on the trained classification model.