Author: Jordi Pages < jordi.pages@pal-robotics.com >

Maintainer: Jordi Pages < jordi.pages@pal-robotics.com >

Support: tiago-support@pal-robotics.com

Source: https://github.com/pal-robotics/tiago_tutorials.git

(!) Please ask about problems and questions regarding this tutorial on answers.ros.org. Don't forget to include in your question the link to this page, the versions of your OS & ROS, and also add appropriate tags.

Face detection (C++)

Description: Example of ROS node embedding OpenCV's face detector.

Keywords: OpenCV

Tutorial Level: ADVANCED

Next Tutorial: Planar object detection and pose estimation

face_detection_title.jpg

Purpose

This tutorial presents a ROS node that subscribes to an image topic and applies the OpenCV face detector based on an Adaboost cascade of Haar features. The node publishes ROIs of the detections and a debug image showing the processed image with the ROIs likely to contain faces.

Pre-Requisites

First, make sure that the tutorials are properly installed along with the TIAGo simulation, as shown in the Tutorials Installation Section.

Download the face detector

In order to execute the demo first we need to download the source code of the face detector. Run the following instructions:

  • cd ~/tiago_public_ws/src
    git clone https://github.com/pal-robotics/pal_face_detector_opencv.git

Building the workspace

Now we need to build the workspace

  • cd ~/tiago_public_ws
    catkin build

Execution

Open four consoles and in each one source the workspace

  • cd ~/tiago_public_ws
    source ./devel/setup.bash

In the first console launch the simulation

  • $ roslaunch tiago_gazebo tiago_gazebo.launch public_sim:=true robot:=steel world:=tutorial_office

Note that in this simulation world there are several person models

gazebo_office_with_people.jpg

In the second console run the face detector node as follows

  • $ roslaunch pal_face_detector_opencv detector.launch image:=/xtion/rgb/image_raw

Moving around

In order to detect faces we need that the robot approaches the persons. In the third console run the key_teleop node as follows

  • $ rosrun key_teleop key_teleop.py

Then, using the arrow keys of the keyboard we can make TIAGo move around the simulated world and approach the different persons.

Watching the detections

In the fourth console we may run an image visualizer to see the face detections

  • $  rosrun image_view image_view image:=/pal_face/debug

face_detections.jpg

Note that faces detected are stroked with a ROI. The detections are not only represented in the /pal_face/debug Image topic but also in /pal_face/faces, which contains a vector with the image ROIs of all the detected faces. In order to see the contents of the topic we may use

  • $  rostopic echo -n 1 /pal_face/faces

which will prompt one message of the topic that when a face is detected will look like

  • header: 
      seq: 0
      stamp: 
        secs: 2582
        nsecs:  37000000
      frame_id: xtion_rgb_optical_frame
    faces: 
      - 
        x: 320
        y: 50
        width: 56
        height: 56
        eyesLocated: False
        leftEyeX: 0
        leftEyeY: 0
        rightEyeX: 0
        rightEyeY: 0
        position: 
          x: 0.0
          y: 0.0
          z: 0.0
        name: ''
        confidence: 0.0
        expression: ''
        expression_confidence: 0.0
        emotion_anger_confidence: 0.0
        emotion_disgust_confidence: 0.0
        emotion_fear_confidence: 0.0
        emotion_happiness_confidence: 0.0
        emotion_neutral_confidence: 0.0
        emotion_sadness_confidence: 0.0
        emotion_surprise_confidence: 0.0
    camera_pose: 
      header: 
        seq: 0
        stamp: 
          secs: 0
          nsecs:         0
        frame_id: ''
      child_frame_id: ''
      transform: 
        translation: 
          x: 0.0
          y: 0.0
          z: 0.0
        rotation: 
          x: 0.0
          y: 0.0
          z: 0.0
          w: 0.0
    ---

Wiki: Robots/TIAGo/Tutorials/FaceDetection (last edited 2017-03-15 14:51:32 by AlessandroDiFava)