Coarse-to-Fine Combinatorial Matching for Dense Isometric Shape Correspondence

Nov 24, 2012

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Coarse-to-Fine Combinatorial Matching for Dense Isometric Shape Correspondence

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A fast local descriptor for dense matching

A fast local descriptor for dense matching. Engin Tola, Vincent Lepetit, Pascal Fua Ecole Polytechnique Federale de Lausanne, Switzerland. Wide baseline stereo . Stereo is called wide baseline if there are significant rotations of the camera translation between camera centers

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Combinatorial Pattern Matching. Outline. Microarrays and Introduction to Clustering Hierarchical Clustering K-Means Clustering Corrupted Cliques Problem CAST Clustering Algorithm . Section 1: Microarrays and Introduction to Clustering. What Is Clustering?.

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A Fast Local Descriptor for Dense Matching

A Fast Local Descriptor for Dense Matching. Engin Tola , Vincent Lepetit , Pascal Fua Computer Vision Laboratory, EPFL Reporter ： Jheng-You Lin. Outline. Introduction DAISY Computation Results C onclusion. Introduction.

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Shape and Matching. Andrew Bender Alexander Cobian. Topics. Approaches Involving New Descriptors Shape Contexts Matching Local Self-Similarities Novel Matching Techniques Pyramid Match Kernel Spatial Pyramid Matching. Shape Contexts (2002).

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Coarse to Fine Grained Sense Disambiguation in Wikipedia. Hui Shen [ Ohio University ] Razvan Bunescu [ Ohio University ] Rada Mihalcea [ University of North Texas ]. *SEM , June 13, 2013. Question Answering. Q: What is the composition of Earth’s atmosphere?.

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Combinatorial Pattern Matching

Combinatorial Pattern Matching. Outline. Week 08: Quiz 2 Hash Tables Repeat Finding Exact Pattern Matching Keyword Trees Suffix Trees Week 09: Heuristic Similarity Search Algorithms Approximate String Matching Filtration Comparing a Sequence Against a Database Algorithm behind BLAST

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Combinatorial Pattern Matching

Combinatorial Pattern Matching. Outline. Hash Tables Repeat Finding Exact Pattern Matching Keyword Trees Suffix Trees Heuristic Similarity Search Algorithms Approximate String Matching Filtration Comparing a Sequence Against a Database Algorithm behind BLAST Statistics behind BLAST

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Combinatorial Pattern Matching

Combinatorial Pattern Matching. An Introduction to Bioinformatics Algorithms (Jones and Pevzner) www.bioalgorithms.info. Genomic Repeats. Example of repeats: A T GGTC TA GGTC CTAGT GGTC Motivation to find them: Genomic rearrangements are often associated with repeats

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Combinatorial Pattern Matching

Combinatorial Pattern Matching. CS 466 Saurabh Sinha. Genomic Repeats. Example of repeats: AT GGTC TA GGTC CTAGT GGTC Motivation to find them: Genomic rearrangements are often associated with repeats Trace evolutionary secrets Many tumors are characterized by an explosion of repeats.

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Combinatorial Pattern Matching

Combinatorial Pattern Matching. CS 466 Saurabh Sinha. Genomic Repeats. Example of repeats: AT GGTC TA GGTC CTAGT GGTC Motivation to find them: Evolutionary annotation Diseases associated with repeats. Genomic Repeats. The problem is often more difficult: AT GGTC TA GG A C CTAGT G T TC

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Lecture 16: Combinatorial Pattern Matching

Lecture 16: Combinatorial Pattern Matching. Study Chapter 9.1 – 9.5. Repeat Finding. Example of repeats: AT GGTC TA GGTC CTAGT GGTC Motivation to find them: Phenotypes arise from copy-number variations Genomic rearrangements are often associated with repeats Trace evolutionary secrets

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Shape Correspondence through Landmark Sliding. Anup Kedia. Introduction. Shape Landmarks. Contd. Landmark Sliding Shape Correspondence Result. Need. Statistical Shape Analysis Accuracy. Different types of Shapes. Supports closed, open, self-crossing and multiple shapes. Input.

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Algorithms for 3D Isometric Shape Correspondence

Algorithms for 3D Isometric Shape Correspondence. Yusuf Sahillioğl u Computer Eng. Dept., Koç University, Istanbul, Turkey. Problem Definition & Apps. Goal: Find a mapping between two shapes. Shape interpolation, animation. Attribute transfer. Shape registration.

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Coarse-to-Fine Combinatorial Matching for Dense Isometric Shape Correspondence

Coarse-to-Fine Combinatorial Matching for Dense Isometric Shape Correspondence. Yusuf Sahillioğlu and Y ücel Yemez Computer Eng. Dept., Koç University, Istanbul, Turkey. Problem Definition & Apps. Goal: Find a mapping between two isometric shapes. Shape interpolation.

380 views • 24 slides

Particle Filters for Shape Correspondence

Particle Filters for Shape Correspondence. Presenter: Jingting Zeng. Outline. Review of Particle Filter How to Use Particle Filters in Shape Correspondence Further Implementation in Shape Clustering. Part One. Review of Particle Filter. What Particle Filter is.

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Coarse-to-Fine Efficient Viterbi Parsing

Coarse-to-Fine Efficient Viterbi Parsing. Nathan Bodenstab OGI RPE Presentation May 8, 2006. Outline. What is Natural Language Parsing? Data Driven Parsing Hypergraphs and Parsing Algorithms High Accuracy Parsing Coarse-to-Fine Empirical Results. What is Natural Language Parsing?.

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A fast local descriptor for dense matching

A fast local descriptor for dense matching. Engin Tola, Vincent Lepetit, Pascal Fua Ecole Polytechnique Federale de Lausanne, Switzerland. Wide baseline stereo. Stereo is called wide baseline if there are significant rotations of the camera translation between camera centers

373 views • 21 slides

Scale Normalization for Isometric Shape Matching

Scale Normalization for Isometric Shape Matching. Yusuf Sahillioğlu and Y ücel Yemez Computer Eng. Dept., Koç University, Istanbul, Turkey. Problem Definition & Scope. Scale problem inherent to isometric shape correspondence. Scale normalization tested by shape correspondence.

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Partial Shape Matching

Partial Shape Matching. Hu Jianwei 2006-10-11. 3D Query. Best Match. 3D Database. Shape Retrieval. Global Shape Matching. Skeleton Based Similarity Reeb Graph Based Similarity Shape Histograms Light Field Descriptor Extended Gaussian Image ……. Partially Overlapping Scans.

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