IP Library Granted Patent US 10,664,706
Granted Patent B2
US 10,664,706 · App. 16/244,419 · Granted May 26, 2020

System and method for detecting, tracking, and classifying objects

Inventors: Don Madden (State College, PA); Ethan Shayne (Sterling, VA)
Assignee: AVIGILON FORTRESS CORPORATION
G06K9/00771G06K2209/23G08G1/015
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Quick Facts
Patent No.
US 10,664,706
App. No.
16/244,419
Granted
May 26, 2020
Kind
B2
Abstract

The present disclosure provides for a method, device, and computer-readable storage medium for performing a method for discerning a vehicle at an access control point. The method including obtaining a video sequence of the access control point; detecting an object of interest from the video sequence; tracking the object from the video sequence to obtain tracked-object data; classifying the object to obtain classified-object data; determining that the object is a vehicle based on the classified-object data; and determining that the vehicle is present in a predetermined detection zone based on the tracked-object data.

Claims (64)

1. A method for discerning a vehicle at an access control point, the method comprising:

obtaining a first video sequence of the access control point from a first camera operable to capture video of the vehicle approaching a first gate;

detecting an object of interest from the first video sequence;

tracking the object from the first video sequence to obtain tracked-object data;

classifying the object as a class of vehicle;

determining that the vehicle is present in a predetermined detection zone of the access control point based on the tracked-object data;

controlling activation of the first gate at the access control point based on at least the class of vehicle;

obtaining a second video sequence of the access control point from a second camera operable to capture video of the vehicle approaching a second gate;

detecting the object of interest from the second video sequence;

tracking the object from the second video sequence; and

controlling activation of the second gate is based on determining if the vehicle is being tailgated.

2. The method of claim 1 , further comprising:

obtaining a third video sequence of the access control point from a third camera operable to capture video of the vehicle between the first gate and the second gate;

detecting the object of interest from the third video sequence; and

tracking the object from the third video sequence.

3. A device for discerning a vehicle at an access control point, the device comprising:

a memory containing instructions; and

at least one processor, operably connected to the memory, that executes the instructions to perform operations comprising:

obtaining a video sequence of the access control point from a first camera operable to capture video of the vehicle approaching a first gate;

detecting an object of interest from the video sequence;

tracking the object from the video sequence to obtain tracked-object data;

classifying the object as a class of vehicle;

determining if the vehicle is being tailgated;

determining that the vehicle is present in a predetermined detection zone of the access control point based on the tracked-object data;

controlling activation of the first gate at the access control point based on at least the class of vehicle;

obtaining a second video sequence of the access control point from a second camera operable to capture video of the vehicle approaching a second gate;

detecting the object of interest from the second video sequence;

tracking the object from the second video sequence;

obtaining a third video sequence of the access control point from a third camera operable to capture video of the vehicle between the first gate and the second pate;

detecting the object of interest from the third video sequence; and

tracking the object from the third video sequence.

4. The device of claim 3 wherein controlling activation of the second gate is based on determining if the vehicle is being tailgated.

5. A method for discerning a vehicle at an access control point, the method comprising:

obtaining a video sequence of the access control point from a first camera operable to capture video of the vehicle approaching a first outer gate;

detecting an object of interest from the video sequence;

tracking the object from the video sequence to obtain tracked-object data;

classifying the object using a neural network classifier to obtain classified-object data;

determining that the object is the vehicle based on the classified-object data;

determining that the vehicle is present in a predetermined detection zone of the access control point based on the tracked-object data;

controlling activation of the first outer gate at the access control point based on at least the determining that the vehicle is present in the predetermined detection zone and the classified-object data;

obtaining a second video sequence of the access control point from a second camera operable to capture video of the vehicle approaching a second gate

detecting the object of interest from the second video sequence;

tracking the object from the second video sequence;

obtaining a third video sequence of the access control point from a third camera operable to capture video of the vehicle between the first gate and the second pate;

detecting the object of interest from the third second video sequence;

tracking the object from the third video sequence; and

controlling activation of a second gate based on determining that the vehicle is present in the predetermined detection zone.

6. A device for discerning a vehicle at an access control point, the device comprising:

a memory containing instructions; and

at least one processor, operably connected to the memory, that executes the instructions to perform operations comprising:

obtaining a video sequence of the access control point from a first camera operable to capture video of the vehicle approaching a first outer gate;

detecting an object of interest from the video sequence;

tracking the object from the video sequence to obtain tracked-object data;

classifying the object using a neural network classifier to obtain classified-object data, wherein the classifying is based on one or more features comprising: Haar-like features, complex cell (C2) features, shape context features, metric size, metric velocity, or trajectory;

determining that the object is the vehicle based on the classified-object data;

determining that the vehicle is present in a predetermined detection zone of the access control point based on the tracked-object data;

controlling activation of the first outer gate at the access control point based on at least the determining that the vehicle is present in the predetermined detection zone and the classified-object data;

obtaining a second video sequence of the access control point from a second camera operable to capture video of the vehicle approaching a second gate;

detecting the object of interest from the second video sequence;

tracking the object from the second video sequence;

obtaining a third video sequence of the access control point from a third camera operable to capture video of the vehicle between the first gate and the second pate;

detecting the object of interest from the third second video sequence;

tracking the object from the third video sequence; and

controlling activation of a second gate based on determining that the vehicle is present in the predetermined detection zone.

Assignments (3)
NUNC PRO TUNC ASSIGNMENT Recorded Oct 23, 2022
From: AVIGILON FORTRESS CORPORATION
To: MOTOROLA SOLUTIONS, INC.
Reel/Frame 061746/0897 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 10, 2019
From: MADDEN, DON; SHAYNE, ETHAN
To: OBJECTVIDEO, INC.
Reel/Frame 047953/0603 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 10, 2019
From: OBJECTVIDEO, INC.
To: AVIGILON FORTRESS CORPORATION
Reel/Frame 047953/0711 →