Learning to Track the Visual Motion of Contours Export

@article{Blake1995, abstract = {A development of a method for tracking visual contours is described. Given an "un-trained" tracker, a training-motion of an object can be observed over some extended time and stored as an image sequence. The image sequence is used to learn parameters in a stochastic differential equation model. These are used, in turn, to build a tracker whose predictor imitates the motion in the training set. Tests show that the resulting trackers can be markedly tuned to desired curve shapes and classes of...}, author = {Blake, Andrew and Isard, Michael and Reynard, David}, citeulike-article-id = {347145}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.7017}, journal = {Artificial Intelligence}, keywords = {ee520, ee520\_part1, filtering, kalman-filtering, tracking}, number = {1-2}, pages = {179--212}, posted-at = {2005-10-10 20:15:35}, priority = {2}, title = {Learning to Track the Visual Motion of Contours}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.7017}, volume = {78}, year = {1995} }

TY - JOUR ID - Blake1995 L3 - citeulike-article-id:347145 N2 - A development of a method for tracking visual contours is described. Given an "un-trained" tracker, a training-motion of an object can be observed over some extended time and stored as an image sequence. The image sequence is used to learn parameters in a stochastic differential equation model. These are used, in turn, to build a tracker whose predictor imitates the motion in the training set. Tests show that the resulting trackers can be markedly tuned to desired curve shapes and classes of... IS - 1-2 JF - Artificial Intelligence EP - 212 TI - Learning to Track the Visual Motion of Contours VL - 78 SP - 179 KW - ee520 KW - ee520_part1 KW - filtering KW - kalman-filtering KW - tracking AU - Blake, Andrew AU - Isard, Michael AU - Reynard, David PY - 1995/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.7017 ER -