PPT-Feature extraction for change detection

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. Feature Extraction MFCCs, which approximate time-varying data by assuming it to be short-time stationary, represent the frequency spectrum and its perception by humans rather accurately, but require a 9300 Harris Corners Pkwy, Charlotte, NC. Why extract features?. Motivation: panorama stitching. We have two images – how do we combine them?. Why extract features?. Motivation: panorama stitching. We have two images – how do we combine them?. 9300 Harris Corners Pkwy, Charlotte, NC. Why extract features?. Motivation: panorama stitching. We have two images – how do we combine them?. Why extract features?. Motivation: panorama stitching. We have two images – how do we combine them?. M . Zubair. . Rafique. Muhammad . Khurram. Khan. Khaled. . Alghathbar. Muddassar. . Farooq. . The 8th FTRA International Conference on . Organics in MST using Micro Extraction with LVI . GC/MS. Method developed by Michael Muramoto. Presentation by Felix Zboralski. Objective & Challenge. . Develop . an Organic Analysis . method that is quick and economical and can be used to support microbial analysis in tracking waste water intrusion into storm water pathways. . 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. 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. Dakun Shen, Ian . Markwood. , Dan Shen, Yao Liu. 1. Mobile Device Theft. 2. Anti-theft Mechanisms. Find My iPhone. GPS. Remotely wipe and lock device. Lock SIM cards. Call the service operators to lock the device. 1. Content. What is . OpenCV. ?. What is face detection and . haar. cascade classifiers?. How to make face detection in Java using . OpenCV. Live Demo. Problems in face detection process. How to improve face detection. Gaussian Distribution. variance. Standard deviation. Statistical representation . and . independence. of random variables. Probability density can be not Gaussian. Variables can be dependent. problems. Jia-Bin Huang, Virginia Tech. Many slides from N Snavely, K. . Grauman. & . Leibe. , and D. Hoiem. Administrative Stuffs. HW 1 posted, due 11:59 PM Sept . 25. Submission through Canvas. Frequently Asked Questions for HW . 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, The correspondence problem. A general pipeline for correspondence. If sparse correspondences are enough, . choose points for which we will search for correspondences (feature points). For each point (or every pixel if dense correspondence), describe point using a . CS5670: Computer Vision. Announcements. Project 1 code due Thursday, 2/25 at 11:59pm. Turnin. via . Github. Classroom. Project 1 artifact due Monday, 3/1 at 11:59pm. Quiz this Wednesday, 2/24, via Canvas.