원문정보
초록
영어
We propose a chapter mark addition method for surgery video application that adopts cubic higher-order local auto-correlation (CHLAC) features. In our method, normal motions, which frequently occur in a scene, are statistically learnt by using CHLAC in combination with the subspace method. An anomalous motion exists far from the subspace of the frequently-observed motions and such motion is detected based on the deviation from the subspace, and a chapter mark is placed just before the position of the detected anomalous motion. We conducted preliminary experiments using surgery video data to confirm effectiveness of the proposed method. The results show that the proposed method can detect the motions not frequently-observed in a surgery operation and the chapters are effectively constructed.
목차
1. Introduction
2. Proposed method
2.1. Scene analysis technique for proposed method
2.2. Cubic higher local auto-correlation (CHLAC)
2.3. Anomalousness detection
2.4. Developed system for proposed method
3. Experiment
3.1. Detected anomalous motion values
3.2. Detected anomalous motions
4. Conclusion
References