Object of Interest Segmentation in Video Sequences with Gaze Data

Object of Interest (OoI) segmentation in video sequences is, due to its temporal and spatial complexity, still a difficult task. Thus, it cannot be done automatically, and interactive segmentation methods are inconvenient and time-consuming. Overcoming these drawbacks and performing OoI segmentation in real-time, this paper introduces a new approach for gaze-based OoI segmentation. The user fixates on the OoI throughout watching a video sequence. The users' gaze provides relevant information on the location of the OoI, which is then used for segmenting the OoI. In comparison to present segmentation methods, our approach notably reduced user-interactions required to attain pixel-accurate segmentations. The first evaluation of our gaze-based OoI segmentation method shows promising results. These are close to, and sometimes even exceeding the quality of the polygon-based ground truth segmentation. In conclusion, these findings encourage further exploration of gaze-based OoI segmentation.