Human Detection from RGB Depth Image using Active contour and Grow-cut Segmentation

In addition to security systems, image/video editing applications demand semantic segmentation of foreground objects. For such high-quality applications, the foreground object's boundary pixels need to be matched accurately.

The proposed method aims for an automated segmentation scheme to detect and segment the human area from an image or video frame and to paste it in another frame/image using image processing techniques using a hybrid analysis of color and depth information. The approach provides a high-quality human factor segmentation scheme that can be used in Chroma keying operations in advanced multimedia editing applications. Depth based analysis along with a series of post-processing stages is employed.