'Visual words' diaporamas de présentation

Clustering with Application to Fast Object Search

03/08/12. Clustering with Application to Fast Object Search. Computer Vision CS 543 / ECE 549 University of Illinois Derek Hoiem. This section. Clustering: grouping together similar points, images, feature vectors, etc. Segmentation: dividing the image into meaningful regions

880 views • 74 slides

Efficient Visual Search for Objects in Videos

Efficient Visual Search for Objects in Videos. Josef Sivic and Andrew Zisserman Presenters: Ilge Akkaya & Jeannette Chang March 1, 2011. Introduction. Image Query. Text Query. Results: Frames. Results: Documents. Generalize text retrieval methods to non-textual information.

779 views • 67 slides

MKL for Category Recognition

843 views • 64 slides

Statistical Object Recognition

CS 636 Computer Vision. Statistical Object Recognition. Nathan Jacobs. Slides adapted from Lazebnik. Administrivia. Project 4 Final Project Next Class is Cancelled. Overview. Statistical Recognition generative vs. discriminative learning Bag of Features Models. Statistical Recognition.

794 views • 60 slides

881 views • 59 slides

Introduction to Computer Vision

611 views • 54 slides

Engaging Visual Learners

Characteristics of Visual Leaners. Engaging Visual Learners. Presentation, Video, Screen Capture. Study Tools. Visualization. Organization. Unused Section Space 1. Unused Section Space 2. Unused Section Space 3. Free Tools for Visual Learners. Debra Geoghan

612 views • 51 slides

Image Retrieval

Image Retrieval. Hao Jiang Computer Science Department 2009. Color Histogram Methods. Color only schemes tend to find many unrelated images. http://amazon.ece.utexas.edu/~qasim/qdialog_IMGDATA2_v1_Birds_Swans.html. Improve Color Histogram Methods.

643 views • 49 slides

Visual Object Recognition

Visual Object Recognition. Bastian Leibe & Computer Vision Laboratory ETH Zurich Chicago, 14.07.2008. Kristen Grauman Department of Computer Sciences University of Texas in Austin. Outline. Detection with Global Appearance & Sliding Windows

645 views • 48 slides

Visual Object Recognition

Visual Object Recognition. Rob Fergus Courant Institute, New York University. http://cs.nyu.edu/~fergus/icml_tutorial/. Agenda. Introduction Bag-of-words models Visual words with spatial location Part-based models Discriminative methods Segmentation and recognition

549 views • 38 slides

Unsupervised Learning of Categorical Segments in Image Collections

The Sixth IEEE Computer Society Workshop on Perceptual Organization in Computer Vision (POCV 2008). Unsupervised Learning of Categorical Segments in Image Collections. *California Institute of Technology **Technion. Marco Andreetto*, Lihi Zelnik-Manor**, Pietro Perona*. Outline.

500 views • 37 slides

Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval

508 views • 36 slides

On Using SIFT Descriptors for Image Parameter Evaluation

On Using SIFT Descriptors for Image Parameter Evaluation. Authors: Patrick M. McInerney 1 , Juan M. Banda 1 , and Rafal A. Angryk 2 1 Montana State University, Bozeman, MT 2 Georgia State University, Atlanta, GA. Introduction.

435 views • 30 slides

Structuring Visual Words in 3D for Arbitrary-View Object Localization

Structuring Visual Words in 3D for Arbitrary-View Object Localization. Jianxiong Xiao, Jingni Chen, Dit-Yan Yeung, and Long Quan Department of Computer Science and Engineering The Hong Kong University of Science and Technology Clear Water Bay, Kowloon, Hong Kong

376 views • 25 slides

Beyond bags of features: Adding spatial information

383 views • 24 slides

Discovering Collocation Patterns: from Visual Words to Visual Phrases

568 views • 15 slides

GRAPHIC DESIGN II

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Introduction

In-Video Product Annotation with Web Information Mining. Guangda Li, Tat-Seng Chua School of Computing, National University of Singapore. Introduction

103 views • 1 slides

Find visual words

136 views • 1 slides

Discovering Objects and their Location in Images

0. 1. 0. 2. Discovering Objects and their Location in Images. Josef Sivic 1 , Bryan C. Russell 2 , Alexei A. Efros 3 , Andrew Zisserman 1 and William T. Freeman 2. 1 Oxford University 2 MIT 3 Carnegie Mellon University. Introduction. The topic discovery models.

71 views • 1 slides