The available edge-based visual odometry methods are sensitive to photometric changes and have instability in edge extraction.Aining at this problem

an edge-fusion-based direct pose estimation method based on depth cameras is proposed.This method combines the advantages of traditional methods and deep learning to extract the edge pixels

which improves the signal to noise ratio（SNR）of edge extraction.Then the extracted edge pixels are used in direct camera pose estimation.A nonparametric statistical method is used to fit the residuals of edge pixels and weights are given

which makes the proposed method more robust to photometric changes.The experimental results on TUM dataset show that this method achieves a good precision of pose estimation.