CHIBA

Name of the competing system: M2HR system

Name and email of the responsible person: Myagmarbayar Nergui ( This e-mail address is being protected from spambots. You need JavaScript enabled to view it )

Date and place: 6/22/2012, Chiba University Japan

Data sources

The following diagram shows that data collection and data processing of out human behavior monitoring robot system. We collected 5 different angle (2 hips, 2 knees and body angle) data from the calculation based on RGB-D image from Kinect sensor, while mobile robot tracking and following human subject from side viewpoints. Then, we preprocessed angle data using quantization method; Hidden Markov Model (HMM) is applied based on the quantized data. Applying HMM, first we collect training data from experiments of different activities, then we test the activities based on the calculated parameters from training process. Finally, our system output is states of the predefined activiteies.

chibaSchema

For each datasource the following table is fulfilled:

Name

Rigth hip angle data

Description of the information measured

Calculated from shoulder center point, right hip point and right knee points extracted from RGB.D image of kinect sensor (Extracted joint points from RGB-D image, which is captured image of tracked human subject attached color markers to his/her lower limb joints).

Units

Degrees

Example values

0-180 degrees

Frequency of generated data in operation

FPS of calculation of angle data is around 13-15.

 

Name

Left hip angle data

Description of the information measured

Calculated from shoulder center point, left hip point and left knee points extracted from RGB.D image of kinect sensor (Extracted joint points from RGB-D image, which is captured image of tracked human subject attached color markers to his/her lower limb joints).

Units

Degrees

Example values

0-180 degrees

Frequency of generated data in operation

FPS of calculation of angle data is around 13-15.

 

Same as above for Right knee angle data and left knee angle data.

Name

Body angle data

Description of the information measured

Calculated from shoulder center point, hip center point and virtual ground point extracted from RGB.D image of kinect sensor (Extracted joint points from RGB-D image, which is captured image of tracked human subject attached color markers to his/her lower limb joints).

Units

Degrees

Example values

0-180 degrees

Frequency of generated data in operation

FPS of calculation of angle data is around 13-15.

DataSets

After, for instance, 30 minutes operation the competitor generates the following data sets:

  1. An array of arrays that include: [time, body angle, left knee angle, right knee angle, left hip angle, right hip angle], every 100ms.
  2. Images data set

Files:

  1. A file containing these samples in mat format
  2. Images got from Kinect.

Devices used during benchmark

Device name

Type

Position in LLab (x,y,z) in meters

Position in user

Input

Output

Communication means to your system

iRobot Create

robot

(shared

control, such as

autonomous

and manual,

controlled by

joystick)

Presence

Track and follow by

actor (we use bigger

than this robot

usually, but for this

competition we

bought iRobot

Create. We are now

deploying our

software on it, but

we are not sure how

it will work, if

possible, please

provide us enough

space to track and

follow actor )

Nearby

actor, and

side

viewpoint

tracking

Kinect

sensor

data

based on

Human

motion

and

obstacles

Control robot

motion

Serial port

2 Kinect

sensors

Presence

-

At Robot

Person moves

Image

Serial port

Color mark

Support (not a device but a garment)

Presence

 

2 Knee, 2 ankle joints

 

 

 

Download datasets

.
 
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