Boosting for Generic 2D/3D Object Recognition

Download or read book Boosting for Generic 2D/3D Object Recognition written by Doaa Abd al-Kareem Mohammed Hegazy and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generic object recognition is an important function of the human visual system. For an artificial vision system to be able to emulate the human perception abilities, it should also be able to perform generic object recognition. In this thesis, we address the generic object recognition problem and present different approaches and models which tackle different aspects of this difficult problem. First, we present a model for generic 2D object recognition from complex 2D images. The model exploits only appearance-based information, in the form of a combination of texture and color cues, for binary classification of 2D object classes. Learning is accomplished in a weakly supervised manner using Boosting. However, we live in a 3D world and the ability to recognize 3D objects is very important for any vision system. Therefore, we present a model for generic recognition of 3D objects from range images. Our model makes use of a combination of simple local shape descriptors extracted from range images for recognizing 3D object categories, as shape is an important information provided by range images. Moreover, we present a novel dataset for generic object recognition that provides 2D and range images about different object classes using a Time-of-Flight (ToF) camera.