I'm looking for a way to identify faces (not specific people, just where the faces are) and track them as they move across a room.
We're trying to measure walking speed for people, and I assumed this would be the easiest way of identifying a person as a person. We'll have a reasonably fast camera for the project, so I can probably use some logic for seeing if "face1 in frame00 == face1 in frame01".
Ideally such a software would return a list of faces (as in x,y locations) and their sizes.
OpenCV. OpenCV is the most popular library for computer vision. Originally written in C/C++, it now provides bindings for Python. OpenCV uses machine learning algorithms to search for faces within a picture.
Build Face Recognition Attendance System using Python Face recognition is a step further to face detection. In face detection, we only detect the location of the human face in an image…
In this operation we use the opencv java to build the application using spring. So in this blog you can see the face detection was successfully done by the application.
Python Module. Automatically find all the faces in an image. Automatically locate the facial features of a person in an image. Recognize faces in images and identify who they are.
Face Recognition module can only be installed for Python version 3.7 and 3.8.
Every reason points towards TensorFlow as the better framework for building face detection and recognition. Still, we must know how the TensorFlow face detector works in building models.
Checkout OpenCV Python Interface
"faint" (The Face Annotation Interface) might be what you're looking for.
http://faint.sourceforge.net/
http://technoroy.blogspot.com/2008/06/faint-search-for-faces.html
I never used it myself. However, I played with the application which bundles with faint.
There was an article about this in the German "Linux Magazin".
They used the Open Computer Vision Library which offers a whole bunch of algorithms to process images in various ways.
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