CV Dazzle vs OpenCV
CV Dazzle vs OpenCV Face Detection: The Results
In this image the dotted lines represent all possible face detections, including false positives, before post-processing. Solid lines indicate a positive face detection. Each of the different colors represent the different Haar Cascade face profiles that were used. Images without any solid lines are classified as false-positives and have beaten the face detector.
Post-processing in OpenCV helps remove false positives. Though false positives are still possible, they are reduced by searching for overlapping detections. Only detections that overlap at least 3 (default) other rectangles are considered to be a face. The default setting can be changed to 2 for a higher detection rate, but with more false positives. Setting the overlap minimum to 0 returns all possible detections, as shown here by the dotted lines.
The solid lines represent the faces. They are confirmed by multiple overlapping rectangles. And the colors correspond to the difference detection profiles. OpenCV includes four robust profiles for detecting faces in a frontal view. These profiles include the “frontalface_default.xml”, “frontalface_alt.xml”, “frontalface_alt2.xml”, and “frontalface_alt_tree.xml” files. Each detector returns different noticeably different results.
OpenCV is a computer vision framework available in many different programming languages. For this test, I used the Java port created for Processing from http://ubaa.net/shared/processing/opencv/opencv_image.html and then confirmed the results using the standard framework in C.
The images on the bottom row without any solid lines indicate that no faces were found. Although some potential faces were found. They were ignored, because there was not enough confidence.
These images show a proof of concept hair + makeup pattern capable of deceiving the OpenCV face detector. It was developed as my master’s thesis project at the Interactive Telecommunication Program at NYU. A more detailed report will be posted on CVDazzle.com when it’s ready.
Model: Jen Jaffe, Hair: Pia Vivas, Makeup: Leigh Brown
