Difference between revisions of "Attention-system-vision"
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=== Demo of face tracking with iCub === | The goal of this group is to identify the face of two persons in front of the iCub. | ||
=== Demo of face tracking with the iCub === | |||
As a starting point, we found out that there is a demo in yarp that is detecting and tracking the face of one human. This demo was implemented by [http://eris.liralab.it/wiki/VVV12_Participants#Ugo_Pattacini Ugo]. Here is a summery of the steps needed to run this demo. | |||
=== Goals === | === Goals === | ||
Latest revision as of 16:06, 24 July 2012
The goal of this group is to identify the face of two persons in front of the iCub.
Demo of face tracking with the iCub
As a starting point, we found out that there is a demo in yarp that is detecting and tracking the face of one human. This demo was implemented by Ugo. Here is a summery of the steps needed to run this demo.
Goals
Ideally, we would like to detect (and not directly track) several faces, so that a specific saliency map can be created and inserted in the visual attention system.
Using openCV to detect faces (or eyes) :
It seems to be possible to detect multiple faces in an image with openCV, using haar transforms, as explained here : http://www.scribd.com/doc/4547752/opencv-objectdetection-2007june10 http://www.cognotics.com/opencv/servo_2007_series/part_2/sidebar.html There seems to be some example code there : http://robotworkshop-kumotek.blogspot.it/2011/04/programming-opencv22-face-detection.html If not using CV_HAAR_FIND_BIGGEST_OBJECT", multiple results (faces) might be returned. Eyes might possibly be detected too : http://python.dzone.com/articles/face-and-eyes-detection-opencv