PPT-Fitting: Deformable contours

Monday Feb 21 Prof Kristen Grauman UTAustin Recap so far Grouping and Fitting Goal move from array of pixel values or filter outputs to a collection of regions objects and shapes. Divvala Alexei A Efros and Martial Hebert Robotics Institute Carnegie Mellon University Abstract The Deformable Parts Model DPM has recently emerged as a very useful and popular tool for tackling the intracategory diversity problem in object detecti Deformable . Mirrors:. a new Adaptive Optics scheme . for . Advanced . Gravitational . Wave Interferometers. Marie Kasprzack. Laboratoire de l’Accélérateur Linéaire. European Gravitational Observatory. Lectures 7 & 8 . – Prof. . Fergus. Slides from: S. Lazebnik, S. Seitz, M. Pollefeys, A. Effros. . How do we build panorama?. We need to match (align) images. Matching with Features. Detect feature points in both images. Akshay Asthana, Jason Saragih, Michael Wagner and Roland G. öcke. ANU, CMU & U Canberra. In part funded by ARC grant TS0669874 . Background. Thinking Head project. http://thinkinghead.edu.au/. 5-year multi-institution (Canberra, UWS, Macquarie, Flinders) project in Australia. a . tyre . onto a wheel. Following simple instructions for correct fitting and user safety. June 2014. N° 9. PRECAUTIONS BEFORE FITTING:. • . Check that the wheel and its components are in good condition. The wheel rim must be . 1. Michael . Maire. . , Pablo . Arbelaez. , . Charless. . Fowlkes. , and . Jitendra. . Malik. university of California, Berkeley – Berkeley. university of California, Irvine - Irvine. Using Contours to Detect and Localize Junctions in Natural Images. for Object Detection. Forrest Iandola, . Ning. Zhang, Ross . Girshick. , Trevor Darrell, and Kurt . Keutzer. Deformable Parts Model (DPM): state of the art algorithm for object detection [1]. Several attempts to accelerate multi-category DPM detection, such as [2] [3]. - Fitting:. Deformable contours. Computer Vision, FCUP, . 20134. Miguel . Coimbra. Slides by Prof. Kristen . Grauman. Deformable contours. a.k.a. active contours, snakes. Given. : initial contour (model) near desired object . Deformable contours. Computer Vision, FCUP, . 2015/16. Miguel Coimbra. Slides by Prof. Kristen . Grauman. Deformable contours. a.k.a. active contours, snakes. Given. : initial contour (model) near desired object . feature-based alignment. Kristen Grauman. UT Austin. Thurs Mar 2. Previously. Interest point detection. Harris corner detector. Laplacian. of Gaussian, automatic scale selection. Invariant descriptors. Matching. Region Representation. Image Alignment, Optical Flow. Lectures . 5 . & . 6. . – Prof. . Fergus. Slides from: S. Lazebnik, S. Seitz, M. Pollefeys, A. Effros. . Panoramas. Facebook 360 photos. 2015. 2. 12.. Jeany Son. References. Bottom-up Segmentation for Top-down . Detection, CVPR 2013. Segmentation-aware Deformable Part Models, CVPR 2014. 2. Prior Works on Segmentation & Recognition. . Shape. . Retrieval. . with . Missing. . Parts. Organizers: . Emanuele . Rodolà. , Or Litany, Michael Bronstein, Alex Bronstein. Motivation. Existing retrieval techniques do not deal well with . We would like to form a higher-level, more compact representation of the features in the image by grouping multiple features according to a simple model. Source: K. Grauman. Fitting. Choose a . parametric model .