The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 27, 2025

Filed:

Apr. 06, 2023
Applicant:

International Institute of Information Technology, Hyderabad, Hyderabad, IN;

Inventors:

Ravi Kiran Sarvadevabhatla, Hyderabad, IN;

Aman Goyal, Ajmer, IN;

Rohit Saluja, Hyderabad, IN;

Dev Agarwal, Jaipur, IN;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 20/54 (2022.01); G06V 10/25 (2022.01); G06V 10/26 (2022.01); G06V 10/766 (2022.01); G06V 10/774 (2022.01); G06V 20/56 (2022.01); G06V 40/10 (2022.01);
U.S. Cl.
CPC ...
G06V 20/54 (2022.01); G06V 10/25 (2022.01); G06V 10/267 (2022.01); G06V 10/766 (2022.01); G06V 10/774 (2022.01); G06V 20/56 (2022.01); G06V 40/10 (2022.01); G06V 2201/08 (2022.01);
Abstract

Provided a method of detecting and tracking a traffic violation of vehicle associated with user through a trapezium shaped object based representation using a deep learning model. The method includes (i) detecting the user and the vehicle to generate a first rectangular bounding box and a second rectangular bounding box of a video, (ii) training the deep learning model by correlating historical trapezium based representations with historical rectangular bounding boxes over historical vehicles, and historical users, (ii) determining a trapezium based representation based on the bounding boxes, (iv) detecting a traffic violation of the vehicle by determining (a) triple-riding violation, if maximum number of intersection of units (IoU) are found by counting the first rectangular bounding box and the second rectangular bounding box, (b) a helmet violation by determining the user without a helmet, and (v) tracking the vehicle that performs the traffic violation based on corresponding trapezium based representation.


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