SYSTEM FOR THREE-DIMENSIONAL OBJECT RECOGNITION AND FOREGROUND EXTRACTION

The present invention describes a system for recognizing objects from color images by detecting features of interest, classifying them according to previous objects' features that the system has been trained on, and finally drawing a boundary around them to separate each object from others in the image. Furthermore, local feature detection algorithms are applied to color images, outliers are removed, and resulting feature descriptors are clustered to achieve effective object recognition. Additionally, the present invention describes a system for extracting foreground objects and the correct rejection of the background from an image of a scene. Importantly, the present invention allows for changes to the camera viewpoint or lighting between training and test time. The system uses a supervised-learning algorithm and produces blobs of foreground objects that a recognition algorithm can then use for object detection/recognition.