IEEE Trans Image Process - Discovering thematic objects in image collections and videos.

Tópicos

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Resumo

Given a collection of images or a short video sequence, we define a thematic object as the key object that frequently appears and is the representative of the visual contents. Successful discovery of the thematic object is helpful for object search and tagging, video summarization and understanding, etc. However, this task is challenging because 1) there lacks a priori knowledge of the thematic objects, such as their shapes, scales, locations, and times of re-occurrences, and 2) the thematic object of interest can be under severe variations in appearances due to viewpoint and lighting condition changes, scale variations, etc. Instead of using a top-down generative model to discover thematic visual patterns, we propose a novel bottom-up approach to gradually prune uncommon local visual primitives and recover the thematic objects. A multilayer candidate pruning procedure is designed to accelerate the image data mining process. Our solution can efficiently locate thematic objects of various sizes and can tolerate large appearance variations of the same thematic object. Experiments on challenging image and video data sets and comparisons with existing methods validate the effectiveness of our method.

Resumo Limpo

given collect imag short video sequenc defin themat object key object frequent appear repres visual content success discoveri themat object help object search tag video summar understand etc howev task challeng lack priori knowledg themat object shape scale locat time reoccurr themat object interest can sever variat appear due viewpoint light condit chang scale variat etc instead use topdown generat model discov themat visual pattern propos novel bottomup approach gradual prune uncommon local visual primit recov themat object multilay candid prune procedur design acceler imag data mine process solut can effici locat themat object various size can toler larg appear variat themat object experi challeng imag video data set comparison exist method valid effect method

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