Spatial-Temporal FAST Corner Detector for Videos
Chia Chun Lee, Yun Chang, Yen‐Yu Lin, Chun-Rong Huang · Frontiers in artificial intelligence and applications · 2015
Due to the increase of large-scale videos, efficient and effective corner detectors are necessary to facilitate video processing and the underlying applications. Designing a good corner detector often faces an accuracy/efficiency trade-off problem. To address this problem, a highly efficient and effective approach named spatial-temporal FAST corner detector is proposed to detecting corners for videos. Our approach considers both the spatial and temporal evidence to extract corners, each of which is an extreme when comparing it with the pixels on the surface of the spatial-temporal tube centered on it. To efficiently obtain spatial-temporal FAST corners, a two-step procedure is adopted. The FAST detector [1] is firstly used to filter out most non-corner pixels. Then, temporal consistency is checked for FAST corners to identify if these corners are spatial-temporal FAST corners. As a result, the detected corners are spatial-temporal coherent. In the experiments, seven the state-of-the-art corner detectors are compared. The results show the superiority of our approach in both repeatability and efficiency.