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Category-independent object detection and localisation plays an important role in many computer vision tasks. In this study, an efficient method is proposed for generic objectness ranking by fusing two dimension (2D) or 3D information. A novel Bayesian model is designed to integrate multimodal cues and global cues to estimate object location, scale and number. In the pure trichannel colour space,...
To detect and localize objects is an indispensable step for many computer vision tasks. Most of the state-of-the-art methods of object detection and localization are category-dependent. These methods can achieve a significant performance. However, they are useless for detecting and localizing objects belonging to an unknown category when applying them to an unknown environment. In this paper, a method...
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