OpenCV Face Detection: Visualized
I take no credit for this video. This is a video created by the absolutely amazing Adam Harvey. I have only uploaded it on my channel because I couldn't find it on YouTube, and some of my students could not access Vimeo. Original url: https://vimeo.com/12774628 Here's the original description with the video at Vimeo: This video visualizes the detection process of OpenCV's face detector. The algorithm uses the Viola Jones method of calculating the integral image and then performing some calculations on all the areas defined by the black and white rectangles to analyze the differences between the dark and light regions of a face. The sub-window (in red) is scanned across the image at various scales to detect if there is a potential face within the window. If not, it continues scanning. If it passes all stages in the cascade file, it is marked with a red rectangle. But this does not yet confirm a face. In the post-processing stage all the potential faces are checked for overlaps. Typically, 2 or 3 overlapping rectangles are required to confirm a face. Loner rectangles are rejected as false-positives. This visualization was done as part of the documentation for CV Dazzle, camouflage from face detection. For more information, visit http://www.cvdazzle.com
I take no credit for this video. This is a video created by the absolutely amazing Adam Harvey. I have only uploaded it on my channel because I couldn't find it on YouTube, and some of my students could not access Vimeo. Original url: https://vimeo.com/12774628 Here's the original description with the video at Vimeo: This video visualizes the detection process of OpenCV's face detector. The algorithm uses the Viola Jones method of calculating the integral image and then performing some calculations on all the areas defined by the black and white rectangles to analyze the differences between the dark and light regions of a face. The sub-window (in red) is scanned across the image at various scales to detect if there is a potential face within the window. If not, it continues scanning. If it passes all stages in the cascade file, it is marked with a red rectangle. But this does not yet confirm a face. In the post-processing stage all the potential faces are checked for overlaps. Typically, 2 or 3 overlapping rectangles are required to confirm a face. Loner rectangles are rejected as false-positives. This visualization was done as part of the documentation for CV Dazzle, camouflage from face detection. For more information, visit http://www.cvdazzle.com