An intelligent depth-based obstacle detection for mobile applications
In this paper, we present a depth-based obstacle detection system in computer vision. Segmentation and noise elimination are adopted to capture different obvious objects. High performance is achieved via obstacle extraction. Our framework can be used to help blind people prevent from dangers and applied to other dynamic surveillance applications. The detection rate is above 93.7% outdoors and indoors.