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I have created a perfect skin detector, but it detects ALL skin. What are my possible options to separate the hands from the rest of the skin?
I don't want to use haar identifiers, so please don't suggest it.
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The OpenCV is a free and open-source library focused on real-time image processing. It can detect and recognize a large variety of objects, but our focus now is to apply techniques and methods to detect and recognize the gestures of a human hand. Methods to detect the gestures of a hand
The researchers at CMU Perceptual Computing Lab have also released models for keypoint detection of Hand and Face along with the body. The Hand Keypoint detector is based on this paper. We will take a quick look at the network architecture and then share code in C++ and Python for predicting hand keypoints using OpenCV. 1. Background
The OpenCV is a free and open-source library focused on real-time image processing. It can detect and recognize a large variety of objects, but our focus now is to apply techniques and methods to detect and recognize the gestures of a human hand.
The skin color detection is one of the most popular methods. This method is simple and depends on skin color that can be white, black, or other colors, and the environment light conditions, as well as the background. Another method doesn’t use the color hand; it uses the convexity detection of OpenCV.
My suggestion is to first segment out the different skin regions through blob detection.
You can then eliminate the unwanted blobs by area and shape thresholding A bit of filtering before these steps would help a lot
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