Real-Time Interactive Segmentation with Superpixel Pre-Segmentation

Image segmentation has been a major research topic in computer vision. It is hard to segment the object from the background fully automatically, and solving the problem leads to the researches in interactive image segmentation, which incorporates user intervention to guide the segmentation process and to correct anomalies in the segmentation results. Although called “interactive,” real-time response is not yet reachable by many recent methods.
In this thesis, we focus on shorten the response time of the segmentation system. To produce real-time result, we propose making use of the time when user interacts with the system. We separate our algorithm into two parts, where the response time is only contributed by the later part. We adopt texture feature to enhance the results in images where foreground and background have similar colors. Experimental results show that our implementation achieves short response time that could be perceived as “instant.” The framework can also be applied by other different algorithms to shorten the response time.