Closed RajkiranVeldur closed 4 years ago
Can someone tell me which pixel this line refers to?
auto depth_in_pixels = (data + pt.y() frame.get_width() + pt.x());
@RajkiranVeldur the depth frame data is stored in units that are called "pixels" here -- there's no standard convention that I know of, so that's the name that was used. Each "pixel" needs to then be scaled to an actual depth (in meters) by using the depth_scale.
@maloel thanks for the response. Does this mean that the variable will return the depth value of the landmark associated with it? For e.g., will it return x-depth value of nose_landmark?
@RajkiranVeldur The variable 'depth_in_pixels' is the depth (not in meters) of that specific landmark, yes. The function iterates thru the landmark indices you give it and averages their depth.
@maloel thanks for replying. We were trying to implement this algorithm using MTCNN instead of Dlib, yet it wasn't accurate. May I know, if you people have tried with any other face detection algorithm?
@maloel OpenVINO is great, however we are more aligned towards MTCNN implementation for facial landmark detection but the accuracy is not even close to Dlib. Our main concern is we are planning to implement it at the edge. So, we are looking for a lightweight model and MTCNN is already lightweight.
Can you please guide us, how we can improve our accuracy with MTCNN based spoof-detection model?
Hi @RajkiranVeldur,
Can you please clarify what you mean by the accuracy issues? Are you referring to the accuracy of the depth you get from realsense, or the accuracy of MTCNN itself (such that the 5 points are off)?
Assuming the latter, it sounds like you need something more along the lines of DLIB's 68-point model which would provide many more points of reference. I did find one project with lightweight 68-point landmark extraction for javascript. Maybe the models it uses can be of use to you?
Hi @maloel yes, I was referring to the accuracy of using MTCNN with Realsense. Most of the time it was showing even a real person as Spoof. Might be, as you said it is because MTCNN gives us very fewer landmarks.
Also, may I get your's or anyone's email from the Realsense team? Actually, we would like to use Realsense with our Facial recognition product. If it is not possible to share here, can you please email me on rajkiran.veldur@techolution.com
Thank you.
Hi @RajkiranVeldur You can send me an email to sergey.dorodnicov@intel.com Any general questions about using the technology are better discussed here, so more people could benefit from it
Hi @dorodnic thank you for sharing the contact details. Can you please help me with the C++ code to display some text on the frame window, depending on the condition?
@RajkiranVeldur Putting text on a DLIB frame is a bit unintuitive. Check here. Let me know if it works :).
@dorodnic @maloel can you tell me what are the landmarks you people are considering for the facial features?
@RajkiranVeldur Putting text on a DLIB frame is a bit unintuitive. Check here. Let me know if it works :).
Hey, @maloel it worked. Thank you :)
@dorodnic @maloel can you please tell me what are the landmarks you are considering for the facial features? Ear, Nose, Eye, Chin and Mouth with respect to the image below.
Hi @RajkiranVeldur
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Face Antispoofing in Python
Can someone help me to conver the below chunk of code to Python. Appreciate your help.