Comment:
Chris
Summary:
This paper shows a system that adapts constelation or 'pictorial structur'model to the recognition of strokes in sketches of particular classes of objects. The model is designed to capture the structure of a particular class of object and is based on local features such as the shape or size of a stroke, and pairwise features, such as distance to other known parts. They uses the a probabilistic model from example sketches with know stroke labelings. The recogniton algorithm determines a maximum-likelihood labeling for an unlabelled sketch by serching through the space of possible label assignments using a multi-pss branch and bound algorithm. For searching, the current recognition process is largely top-down based
Discussion:
The paper seems interesting to me. Which is good paper for dealing with sketched picture. They use spatial information for recogniton, more specifically, use the spatial relathionship between each part. However, when then individual part is not correct, does the system can detect it?
It uses a statical model, ifthe individual part is too far, "away" from the statitical center. It will be rejected by the model.
ReplyDelete