A novel method for the simultaneous modeling and tracking (SMAT) of a feature set during motion sequence is proposed. The method requires no prior information. Instead the a posteriori distribution of appearance and shape is built up incrementally using an exemplar based approach. The resulting model is less optimal than when a priori data is used, but can be built in real-time. Data in any form may be used, provided a distance measure and a means to classify outliers exists. Here, a two tier implementation of SMAT is used: at the feature level, mutual information is used to track image patches; and at the object level, a structure model is built from the feature positions. As experiments demonstrate, the tracker is robust and operates in real-time without requiring prelearned data.
Simultaneous modeling and tracking (SMAT) of feature sets
2005-01-01
422075 byte
Conference paper
Electronic Resource
English
SLS Subscale Model Acoustic Test Program (SMAT)
NTRS | 2014
|Ultrasonic Measurement of Residual Stress in SMAT Metals
SAE Technical Papers | 2006
|