'Www vision caltech' presentation slideshows

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.

795 views • 60 slides

Introduction to Object Recognition

CS 636 Computer Vision. Introduction to Object Recognition. Nathan Jacobs. Slides adapted from Lazebnik. Object Recognition: History and Overview. Slides adapted from Fei-Fei Li, Rob Fergus, Antonio Torralba , and Jean Ponce. ~10,000 to 30,000 visual categories. OBJECTS. INANIMATE.

601 views • 44 slides

Bag-of-features models

Bag-of-features models. Origin 1: Texture recognition. Texture is characterized by the repetition of basic elements or textons For stochastic textures, it is the identity of the textons, not their spatial arrangement, that matters.

440 views • 27 slides

Bag-of-features models

Bag-of-features models. Origin 1: Texture recognition. Texture is characterized by the repetition of basic elements or textons For stochastic textures, it is the identity of the textons, not their spatial arrangement, that matters.

458 views • 27 slides

Computer Vision CS 776 Spring 2014

Computer Vision CS 776 Spring 2014. Recognition Machine Learning Prof. Alex Berg. Recognition: A machine learning approach. Slides adapted from Svetlana Lazebnik , Fei -Fei Li, Alex Berg, Rob Fergus, Antonio Torralba , Kristen Grauman , and Derek Hoiem.

388 views • 26 slides

Recognition: A machine learning approach

434 views • 24 slides

Recognition: A machine learning approach

415 views • 24 slides