Facial Keypoints Detection
This work addresses facial keypoint detection for face recognition applications, but it appears incremental as it applies existing methods without introducing new techniques.
The paper tackles the problem of detecting facial keypoints for face recognition by studying various algorithms, including linear regression, tree-based models, neural networks, and CNNs, and demonstrates effectiveness through experiments on a dataset.
Detect facial keypoints is a critical element in face recognition. However, there is difficulty to catch keypoints on the face due to complex influences from original images, and there is no guidance to suitable algorithms. In this paper, we study different algorithms that can be applied to locate keyponits. Specifically: our framework (1)prepare the data for further investigation (2)Using PCA and LBP to process the data (3) Apply different algorithms to analysis data, including linear regression models, tree based model, neural network and convolutional neural network, etc. Finally we will give our conclusion and further research topic. A comprehensive set of experiments on dataset demonstrates the effectiveness of our framework.