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https://github.com/linas/perception
Perception synthesizer
https://github.com/linas/perception
Last synced: about 1 month ago
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Perception synthesizer
- Host: GitHub
- URL: https://github.com/linas/perception
- Owner: linas
- License: lgpl-2.1
- Created: 2014-12-16T23:07:17.000Z (about 10 years ago)
- Default Branch: master
- Last Pushed: 2016-02-19T14:02:26.000Z (almost 9 years ago)
- Last Synced: 2024-10-20T10:31:17.502Z (2 months ago)
- Language: Python
- Size: 48.8 KB
- Stars: 0
- Watchers: 3
- Forks: 13
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
Perception Synthesizer
======================
Planned function: accept video (pi_vision) from multple sources, convert
to 3D spatial coordinates using ros-tf. Publish intersting events to all
concerned. Interesting events include:
* Entry, exit of a human face in the field of view.
* Location of the face.
There are several goals to be acheived:
* Integrate multiple camera inputs. In particular, the eye cameras move
with the eyes, and thus have a constantly changing field-of-view,
whereas the body camera has an essentially fixed field-of-view. The
information from these sources needs to be integrated.
* Behaviour nodes that need perception information should be able to
to poll for it on an as-needed basis, rather than being driven by
a 20-frames-per-second perception updates.
##Prerequisites
pi_vision is needed. See
[pi_vision](https://github.com/hansonrobotics/pi_vision) for details.
## Running, Testing
There are several ways to get things running. One way is to manually
start the usb camera node, and the pi_vision node, and then the
perception node. A simpler alternative is to use the provided launch
files to do this automatically. So:
### Single (body) camera startup
Just run the launch files. You may want to adjust single-cam.launch
to match your actual webcam.
```
roslaunch perception tracker-single-cam.launch
roslaunch perception geometry.launch
```
### Two-camera (body+eye) startup
```
roslaunch perception tracker.launch
roslaunch perception geometry.launch
```
### Disable rviz visualization
The rviz visualizer can be disabled by saying:
```
roslaunch perception geometry.launch gui=false
```
### Alternative URDF files:
Alternative URDF files can be specified by saying
```
roslaunch perception geometry.launch model:=other.urdf
```
to use the `other.urdf` file.
### Manual startup
* Make sure the usb camera is running, typically like this:
```
roslaunch ros2opencv usb_cam.launch
```
* Make sure pi_vision is running:
```
roslaunch pi_face_tracker face_tracker_usb_cam.launch
```
* Make sure that the face tracker is publishing faces:
```
rostopic echo /camera/face_locations
```
* Start the perception node:
```
rosrun perception faces_tf2_broadcaster.py
```
* Verify that the 3D location of the face is reasonable; launch rviz to
see where it is.
```
rosrun rviz rviz -d `rospack find perception`/rviz/faces.rviz
```
## ROS Nodes
### faces_tf2_broadcaster
Broadcast `/tf` data from face tracking.
###### Subscribed topics
* `camera/face_locations (pi_vision/Faces)`: Faces published by
pi_vision, as seen by main camera.
* `eye_camera/face_locations (pi_vision/Faces)`: Faces published by
pi_vision, as seen by eye camera.
###### Params topics
* `max_distance`: Max distance for faces from eye-camera and body
camera to be considered same.
###### Transformations published:
* `face_base`: Face location based on body camera
* `Face`: Transformation relative to the `face_base` from eye
camera.
###### Testing
* Make sure you have two cameras connected:
- Body Camera on `/dev/video2`
- Eye Camera on `/dev/video1`
* Run face tracking: `roslaunch perception tracker.launch`
* Run the node: `roslaunch perception display.launch`