Depth sensor based passenger sensing for passenger conveyance control

Patent metadata

Field	Value
Publication number	US-2016289042-A1
Application number	US-201615089609-A
Country	US
Kind code	A1
Filing date	Apr 4, 2016
Priority date	Apr 3, 2015
Publication date	Oct 6, 2016
Grant date	—

Abstract

A passenger conveyance system includes a depth-sensing sensor for capturing depth map data of objects within a field of view adjacent a passenger conveyance door. A processing module 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, and a passenger conveyance controller to receive the passenger data from the processing module, wherein the passenger conveyance controller controls a passenger conveyance dispatch control function in response to the passenger data

First claim

1 - 25 . (canceled)

26 . A passenger conveyance system, comprising:
a depth-sensing sensor for capturing depth map data of objects within a field of view adjacent a passenger conveyance door; a processing module in operable communication with the depth-sensing sensor to receive the depth map data, the processing module using the depth map data to track an object and calculate passenger data associated with the tracked object; and a passenger conveyance controller to receive the passenger data from the processing module, wherein the passenger conveyance controller controls a passenger conveyance dispatch control function in response to the passenger data.

27 . The system as recited in claim 26 , wherein the depth map data is 3D depth map data.

28 . The system as recited in claim 27 , wherein the depth-sensing sensor comprises 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), or a combination comprising at least one of the foregoing.

29 . The system as recited in claim 28 , wherein the field-of-view is about 180 degrees.

30 . The system as recited in claim 29 , wherein the processing module determines an object parameter of the tracked object, wherein the object parameter comprises an object count, a location, a size, a direction, an acceleration, a velocity, an object classification, or a combination comprising at least one of the foregoing.

31 . The system as recited in claim 30 , wherein the processing module is in communication with the passenger conveyance controller and communicates the object parameter of the tracked object to the passenger conveyance controller.

32 . The system as recited in claim 30 , wherein the processing module determines the passenger data based on the object parameter of the tracked object, wherein the passenger data provided to the passenger conveyance controller comprises an estimated arrival time, a probability of arrival, a covariance, a number of passengers waiting for a passenger conveyance, or a combination comprising at least one of the foregoing.

33 . The system as recited in claim 32 , wherein the object parameter of the tracked object comprises object classification and the processing module calculates the passenger data if the object classification comprises a passenger.

34 . The system as recited in claim 33 , wherein the processing module divides the field of view of the depth sensing sensor into a first region and a second region, wherein the second region is defined as an area adjacent the passenger conveyance door.

35 . The system as recited in claim 34 , wherein the passenger data comprises a number of passengers waiting for a passenger conveyance, and wherein the processing module increments the number of passengers waiting for a passenger conveyance based on a number of tracked objects that enter the second region.

36 . The system as recited in claim 35 , wherein the depth-sensing sensor is located on a wall adjacent to the passenger conveyance door.

37 . The system as recited in claim 36 , wherein the depth-sensing sensor is located at about knee height.

38 . The system as recited in claim 37 , wherein the depth-sensing sensor is located at 150 mm to 700 mm from an adjacent floor.

39 . The system as recited in claim 38 , wherein the field of view comprises a passenger waiting area, adjacent to the passenger conveyance door.

40 . The system as recited in claim 39 , wherein the field of view comprises the passenger conveyance door and an area at least partially surrounding the passenger conveyance door.

41 . A method of providing video aided data for use in passenger conveyance control, the method comprising:
detecting an object located in a field of view of a depth-sensing sensor; tracking the object based on distance to the passenger conveyance door; calculating passenger data associated with the tracked object; communicating the passenger data to a passenger conveyance controller; and controlling a passenger conveyance cab with the passenger conveyance controller in response to the passenger data.

42 . The method as recited in claim 41 , wherein controlling the passenger conveyance cab further comprises opening the passenger conveyance door, moving the passenger conveyance cab, stopping the passenger conveyance cab, redirecting the passenger conveyance cab, or a combination comprising at least one of the foregoing.

43 . The method as recited in claim 42 , wherein controlling further comprises dispatching two or more passenger conveyance cabs substantially simultaneously in response to the passenger data.

44 . The method as recited in claim 43 , wherein calculating passenger data includes calculating an object parameter for the tracked object, wherein the object parameter includes location, a size, a velocity, a direction, an acceleration, an object classification, or a combination comprising at least one of the foregoing.

45 . The method as recited in claim 42 , wherein calculating passenger data comprises background subtraction.

46 . The method as recited in claim 42 , wherein calculating passenger data comprises frame differencing.

47 . The method as recited in claim 42 , wherein calculating passenger data comprises spurious data rejection.

48 . The method as recited in claim 46 , wherein spurious data rejection includes:
computing a depth background; segmenting a foreground object; removing a foreground region; segmenting a moving object by a 3D morphological operation; transforming the moving object to 3D world coordinates; estimating an actual height and actual volume of the moving object; and removing a spurious moving object from a scene boundary by geometric filtering.

49 . The method as recited in claim 47 , wherein the 3D morphological operation comprises computing a 2D foreground object by depth background subtraction, size filtering on a mask as a function of range; connecting mask regions; segmenting objects in 3D based on depth discontinuity, or a combination comprising at least one of the foregoing.

50 . The method as recited in claim 48 , wherein the 2D foreground object within the mask is at any depth.

Assignees

• Otis Elevator Co

Inventors

• Fang Hui
• Hsu Arthur
• Finn Alan Matthew
• Jia Zhen

Classifications

• G06F18/24

  Classification techniques · CPC title

• G06T7/194

  involving foreground-background segmentation · CPC title

• G06T2200/04

  involving 3D image data · CPC title

• G06T7/73

  using feature-based methods · CPC title

• G06T7/10

  Segmentation; Edge detection (motion-based segmentation G06T7/215) · CPC title