Scale Invariance, Local Descriptors, SIFT
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00:00:00
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Lecture 13: Local Features II |
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00:00:05
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Course Outline |
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00:01:19
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Recap: Local Feature Matching Outline |
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00:03:31
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Recap: Requirements for Local Features |
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00:04:17
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Recap: Harris Detector [Harris88] |
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00:06:40
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Recap: Harris Detector Responses [Harris88] |
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00:09:28
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Recap: Hessian Detector [Beaudet78] |
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00:10:39
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Recap: Hessian Detector Responses [Beaudet78] |
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00:11:26
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Topics of This Lecture |
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00:12:28
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From Points to Regions... |
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00:13:45
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Naïve Approach: Exhaustive Search |
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00:16:04
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Automatic Scale Selection |
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00:22:54
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What Is A Useful Signature Function? |
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00:26:30
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Characteristic Scale |
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00:27:22
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Laplacian-of-Gaussian (LoG) |
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00:40:11
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LoG Detector: Workflow |
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00:44:56
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Difference-of-Gaussian (DoG) |
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00:47:37
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Key point localization with DoG |
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00:48:59
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DoG - Efficient Computation |
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00:57:45
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Results: Lowe's DoG |
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01:00:28
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Harris-Laplace [Mikolajczyk '01] |
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01:03:21
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Summary: Scale Invariant Detection |
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01:04:41
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Topics of This Lecture |
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01:05:01
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Rotation Invariant Descriptors |
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01:06:05
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Orientation Normalization: Computation |
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01:09:14
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Topics of This Lecture |
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01:09:28
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The Need for Invariance |
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01:11:54
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Affine Adaptation |
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01:14:46
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Iterative Affine Adaptation |
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01:15:46
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Affine Normalization/Deskewing |
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01:16:43
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Affine Adaptation Example |
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01:17:22
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Summary: Affine-Inv. Feature Extraction |
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01:17:52
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Invariance vs. Covariance |
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01:20:23
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Topics of This Lecture |
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01:20:38
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References and Further Reading |