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Visual Learning and Recognition: Difference between revisions
Visual Learning and Recognition (view source)
Revision as of 22:19, 3 December 2020
, 3 December 2020→Discriminatively Trained Part Based Models (DPM)
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* <math>w_{ij}^T \in \mathbb{R}^5</math> is the deformation parameter between parts i and j | * <math>w_{ij}^T \in \mathbb{R}^5</math> is the deformation parameter between parts i and j | ||
The total number of configurations is <math>10^(4*N)</math> since for each <math>100\ | The total number of configurations is <math>10^{(4*N)}</math> since for each <math>100 \times 100</math> image, each of <math>p_i</math> can take 100*100 values. <math>N</math> is the number of parts. | ||
The trick is to use dynamic programming and a tree-based model. | The trick is to use dynamic programming and a tree-based model. | ||