直接法和间接法:最小化光度误差vs最小化重投影误差 而两者的处理流程区别在于: 间接法(分步进行) 首先将raw sensor measurements预处理后生成intermediate representation从而先解决一部分问题(先找几何对应关系) 该步通常以提取特征点为主但是也有其他的方法 如以dense,regularized optical flow来建立raw sensor measureme...
While sparse signal, e.g., LiDAR and Radar, has been leveraged as guidance for enhancing dense depth es- timation, the improvement is limited due to its low density and imbalanced distribution. To maximize the utility from the sparse source, we propose Sparse S...
Most state-of-the-art methods heavily rely on dense optical flow as motion representation. Although combining optical flow with RGB frames as input can achieve excellent recognition performance, the optical flow extraction is very time-consuming. This undoubtably will count against real-time action ...
Dense structural learning for infrared object tracking at 200+ Frames per Second. Pattern Recognit. Lett. 2017, 100, 152–159. [Google Scholar] [CrossRef] Berg, A.; Ahlberg, J.; Felsberg, M. Channel coded distribution field tracking for thermal infrared imagery. In Proceedings of the IEEE...