Learning Features for Object Discovery: An Unsupervised Approach

碩士 === 國立清華大學 === 資訊工程學系 === 104 === The task of object discovery is to gure out common categories of objects in multiple images without prior knowledge of object categories. It is considered as very challenging computer vision problem. Given a set of images, we aim to identify and localize the comm...

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Bibliographic Details
Main Authors: Fang, Chun, 方鈞
Other Authors: Chen, Hwann Tzong
Format: Others
Language:en_US
Published: 2016
Online Access:http://ndltd.ncl.edu.tw/handle/16559322939509009527
Description
Summary:碩士 === 國立清華大學 === 資訊工程學系 === 104 === The task of object discovery is to gure out common categories of objects in multiple images without prior knowledge of object categories. It is considered as very challenging computer vision problem. Given a set of images, we aim to identify and localize the common objects. The common objects may vary in scales, poses, appearances, and with occlusions, and these variations make the task of object discovery more diffcult. Conventional solutions tackle the problem with the aid of human intervention. In this work, we present an unsupervised method to learn effective features for object discovery.