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Bayesian Optimization For Refining Object Proposals, With An Application To Pedestrian Detection, Anthony D. Rhodes
Bayesian Optimization For Refining Object Proposals, With An Application To Pedestrian Detection, Anthony D. Rhodes
Student Research Symposium
We devise an algorithm using a Bayesian optimization framework in conjunction with contextual visual data for the efficient localization of objects in still images. Recent research has demonstrated substantial progress in object localization and related tasks for computer vision. However, many current state-of-the-art object localization procedures still suffer from inaccuracy and inefficiency, in addition to failing to successfully leverage contextual data. We address these issues with the current research.
Our method encompasses an active search procedure that uses contextual data to generate initial bounding-box proposals for a target object. We train a convolutional neural network to approximate an offset distance …