PDF-Descriptor/Feature Extraction

Shape Techniques Fred Park UCI iCAMP 2011 Outline 1 Overview and Shape Representation 2 Shape Descriptors Shape Parameters 3 Shape Descriptors as 1D Functions Dimension Reducing Signatures of s. Gerald Nielson. Overview. What is Augmented Reality?. Types of AR. Computer Vision overview . Future . of Augmented Reality. AR development. Augmented . Virtuality. - the . merging of real world objects into virtual worlds. Image from http://graphics.cs.cmu.edu/courses/15-463/2010_fall/. Robust feature-based alignment. So far, we’ve assumed that we are given a set of “ground-truth” correspondences between the two images we want to align. Can you detect an abrupt change in this picture?. Ludmila. I . Kuncheva. School of Computer Science. Bangor University. Answer – at the end. Plan. Zeno says there is no such thing as change.... If change exists, is it a good thing?. 3 types of descriptors. :. SIFT / PCA-SIFT . (. Ke. , . Sukthankar. ). GLOH . (. Mikolajczyk. , . Schmid. ). DAISY . (. Tola. , et al, Winder, et al). Comparison of descriptors . (. Mikolajczyk. The full standard initiative is located at . www.voicebiometry.org. Quick description. Standard manual with detailed description and a quick user guide to…. The reference demo package. Contains full speaker-recognition (demo) pipeline. Image from http://graphics.cs.cmu.edu/courses/15-463/2010_fall/. A look into the past. http://blog.flickr.net/en/2010/01/27/a-look-into-the-past/. A look into the past. Leningrad during the blockade. electroencephalographic records . using . EEGFrame . framework. Alan Jović, Lea Suć, Nikola Bogunović. Faculty of Electrical Engineering and Computing, University of Zagreb. Department of Electronics, Microelectronics, Computer and Intelligent Systems. CS5670: Computer Vision. Noah Snavely. Reading. Szeliski: 4.1. Announcements. Project 1 Artifacts due tomorrow, Friday 2/17, at 11:59pm. Project 2 will be released next week. In-class quiz at the beginning of class Thursday. Corpus. Tool. Martin Weisser. Research . Center. for Linguistics & Applied Linguistics. Guangdong University of Foreign Studies. weissermar@gmail.com. Outline. Genesis of the Tool. Feature . Overview. Principle Component Analysis. Why Dimensionality Reduction?. It becomes more difficult to extract meaningful conclusions from a data set as data dimensionality increases--------D. L. . Donoho. Curse of dimensionality. Gaussian Distribution. variance. Standard deviation. Statistical representation . and . independence. of random variables. Probability density can be not Gaussian. Variables can be dependent. problems. James Hays. cs195g Computational Photography. Brown University, Spring 2010. Recap from Monday. What imagery is available on the Internet. What different ways can we use that imagery. aggregate statistics. Finge sing Ridges and Valleys Paramvir Singh * Department of Computer Engineering Punjabi University Patiala, India Dr. Lakhwinder Kaur Department of Computer Engineering Punjabi University Patiala, Basic correspondence. Image patch as descriptor, NCC as similarity. Invariant to?. Photometric transformations?. Translation?. Rotation?. Scaling?. Find dominant orientation of the image patch. This is given by .