A Novel Depth Map Generation Method Based on K-means Clustering
Siming Meng, Hao Jiang · 2012
In this paper, we propose a novel depth map generation method. After a series of pre-treatment process, image quality capture and bilateral filtering, K-means clustering method has been used for classification of background and front objects. Then the depth map could be generated directly depend on the predeterminate model which is given a forehand, finally the correct depth map can be vividly created base on the layer Stratifying. The experiment result shows that the depth map directly represent the depth information and also earn good subjective evaluation.