IP Library Granted Patent US 10,513,416
Granted Patent B2
US 10,513,416 · App. 15/089,612 · Granted Dec 24, 2019

Depth sensor based passenger sensing for passenger conveyance door control

Inventors: Hui Fang (Shanghai, CN); Arthur Hsu (South Glastonbury, CT); Alan Matthew Finn (Hebron, CT); Zhen Jia (Shanghai, CN)
Assignee: Otis Elevator Company
B66B1/468B66B1/3461B66B13/146B66B13/26G05B19/042G06T7/50G06T15/04B66B2201/20B66B2201/214B66B2201/4638G05B2219/2659G06T2207/10028
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Quick Facts
Patent No.
US 10,513,416
App. No.
15/089,612
Filed
Apr 4, 2016
Granted
Dec 24, 2019
Kind
B2
Art Unit
2837
USPC
187/316
Abstract

An passenger conveyance system includes a depth-sensing sensor within a passenger conveyance enclosure for capturing depth map data of objects within a field of view that includes a passenger conveyance door. A processing module is in communication with the depth-sensing sensor to receive the depth map data, the processing module uses the depth map data to track an object and calculate passenger data associated with the tracked object. a passenger conveyance controller receives the passenger data from the processing module to control operation of a passenger conveyance door in response to the passenger data.

Claims (41)

1. A passenger conveyance system, comprising:

a depth-sensing sensor for capturing 3D depth map data of objects within a field of view that comprises a passenger conveyance door and a waiting area adjacent to the passenger conveyance door;

a processing module in communication with the depth-sensing sensor to receive the 3D depth map data, the processing module uses the 3D depth map data to track an object and calculate passenger data associated with the tracked object; and

a passenger conveyance controller in communication with the processing module to receive the passenger data, the passenger data comprises an estimated arrival time and a number of passengers waiting for a passenger conveyance cab, to control a door dwell time of a passenger conveyance door in response to the passenger data.

2. The system as recited in claim 1 , wherein the depth-sensing sensor comprises at least one of a structured light measurement, phase shift measurement, time of flight measurement, stereo triangulation device, sheet of light triangulation device, light field cameras, coded aperture cameras, computational imaging techniques, simultaneous localization and mapping (SLAM), imaging radar, imaging sonar, scanning LIDAR, flash LIDAR, Passive Infrared (PIR) sensor, and small Focal Plane Array (FPA).

3. The system as recited in claim 2 , wherein the processing module calculates at least one of the following object parameters with respect to the tracked object, including: location, size, direction, acceleration, velocity, and object classification.

4. The system as recited in claim 3 , wherein the processing module provides the object parameters to the passenger conveyance controller.

5. The system as recited in claim 4 , wherein the processing module calculates the passenger data based on the object parameters, wherein the passenger data comprises at least one of a probability of arrival, and a covariance.

6. The system as recited in claim 1 , wherein the processing module calculates the passenger data if the tracked object is classified as a passenger.

7. The system as recited in claim 6 , wherein the processing module calculates the passenger data with respect to the passenger conveyance doors.

8. The system as recited in claim 7 , wherein the processing module calculates the passenger data with respect to a distance of a passenger to the passenger conveyance doors.

9. The system as recited in claim 8 , wherein the passenger conveyance controller delays closing of the passenger conveyance doors in response to the passenger data.

10. The system as recited in claim 8 , wherein the passenger conveyance controller delays opening of the passenger conveyance doors in response to the passenger data.

11. The system as recited in claim 8 , wherein the passenger conveyance controller hastens closing of the passenger conveyance doors in response to the passenger data.

12. A method of providing video aided data for use in passenger conveyance control, the method comprising:

detecting an object located in an area adjacent to a passenger conveyance door;

tracking the object based on distance to the passenger conveyance door;

calculating passenger data associated with the tracked object, the passenger data comprises an estimated arrival time, and a number of passengers waiting for a passenger conveyance; and

providing the passenger data to a passenger conveyance controller, wherein the passenger conveyance controller causes a passenger conveyance door to be controlled to control a door dwell time in response to the passenger data.

13. The method as recited in claim 12 , further comprising causing passenger conveyance doors to be opened in response to the passenger data.

14. The method as recited in claim 13 , further comprising causing passenger conveyance doors to be closed in response to the passenger data.

15. The method as recited in claim 14 , wherein the passenger conveyance controller delays closing of the passenger conveyance doors in response to the passenger data.

16. The method as recited in claim 15 , wherein the passenger conveyance controller delays opening of the passenger conveyance doors in response to the passenger data.

17. The method as recited in claim 16 , wherein the passenger conveyance controller hastens closing of the passenger conveyance doors in response to the passenger data.

18. The method as recited in claim 17 , wherein calculating passenger data includes: calculating at least one of the following object parameters for the tracked object, including: location, size, velocity, direction, acceleration, and object classification.

19. The method as recited in claim 18 , wherein calculating passenger data includes: background subtraction.

20. The method as recited in claim 19 , wherein calculating passenger data includes: frame differencing.

21. The method as recited in claim 20 , wherein calculating passenger data includes: spurious data rejection.

22. The method as recited in claim 21 , wherein spurious data rejection includes:

computing a depth background to segment foreground objects;

removing isolated foreground regions and segment moving objects for further analysis via 3D morphological operations;

transform moving objects to 3D world coordinates to estimate actual heights and volumes; and

remove spurious moving objects from the scene boundary via geometric filtering.

23. The method as recited in claim 22 , wherein the 3D morphological operations includes:

computing a 2D foreground object by depth background subtraction;

size filtering on the mask as a function of range;

connect mask regions; and

segmenting objects in 3D based on depth discontinuity.

24. The method as recited in claim 23 , wherein the 2D foreground objects within the mask can be at any depth.

25. The method as recited in claim 12 , further comprising using an ETA (estimated time of arrival) from a distance between a kiosk and the passenger conveyance, the ETA used for adjusting the dwell time.

26. The method as recited in claim 12 , further comprising adjusting the dwell time with respect to dispatching of an elevator car.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 27, 2016
From: FANG, HUI; HSU, ARTHUR; FINN, ALAN MATTHEW; JIA, ZHEN
To: OTIS ELEVATOR COMPANY
Reel/Frame 040153/0513 →
Priority Claims (1)
CN 2015 1 0158642 · Apr 19, 2016 · national
Continuity (1)
Related Publication 20160289043A1 · Oct 6, 2016
Cited By (1)
US 12,261,448