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| May 8
| May 8
| Garrett Warnell
| Garrett Warnell
| TBA
| Two-Dimensional Phase Unwrapping for Interferometric Synthetic Aperture Radar
|-
|-
| May 15
| May 15
| Sumit Sekhar
| Sumit Sekhar
| TBA
| Sparse methods for robust and efficient recognition
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|}
Interactive object segmentation has great practical importance in computer vision. Many interactive methods have been proposed utilizing user input in the form of mouse clicks and mouse strokes, and often requiring a lot of user intervention. In this paper, we present a system with a far simpler input method: the user needs only give the name of the desired object. With the tag provided by the user we do a text query of an image database to gather exemplars of the object. Using object proposals and borrowing ideas from image retrieval and object detection, the object is localized in the target image. An appearance model generated from the exemplars and the location prior are used in an energy minimization framework to select the object. Our method outperforms the state-of-the-art on existing datasets and on a more challenging dataset we collected.
Interactive object segmentation has great practical importance in computer vision. Many interactive methods have been proposed utilizing user input in the form of mouse clicks and mouse strokes, and often requiring a lot of user intervention. In this paper, we present a system with a far simpler input method: the user needs only give the name of the desired object. With the tag provided by the user we do a text query of an image database to gather exemplars of the object. Using object proposals and borrowing ideas from image retrieval and object detection, the object is localized in the target image. An appearance model generated from the exemplars and the location prior are used in an energy minimization framework to select the object. Our method outperforms the state-of-the-art on existing datasets and on a more challenging dataset we collected.
===Two-Dimensional Phase Unwrapping for Interferometric Synthetic Aperture Radar===
Speaker: [http://garrettwarnell.com/ Garrett Warnell] -- Date: May 8, 2014
In this talk, I will focus on the topic of two-dimensional phase unwrapping for interferometric synthetic aperture radar (InSAR). I will give an overview of InSAR and the phase unwrapping problem, and review several classes of methods that have been proposed to solve it. I will then discuss the relationship between this problem and the common computer vision problem of depth inference from gradients. I'll conclude by discussing my ongoing work that formulates phase unwrapping as a sparse error correction problem.
===Sparse methods for robust and efficient recognition===
Speaker: [http://www.umiacs.umd.edu/~sshekha/ Sumit Shekhar] -- Date: May 15, 2014
In this talk, I will talk of two problems in visual recognition. In the first part, I will talk about the problem of low resolution face recognition. This problem can happen in many scenarios like surveillance where the probe images are low resolution, but a high resolution gallery image is available. I will describe a synthesis based approach for low resolution recognition and demonstrate results on different face datasets. In the second part, I will describe a new analysis framework for sparse coding which has recently started getting attention. I will describe its application to various recognition problems and also demonstrate that its more efficient than standard sparse coding framework.
