1. An active learning system for fingerprinting an object in an image frame, comprising: one or more processors that include: an oriented localized filter module being configured to extract local features from a potential object candidate within the image frame by receiving an object model of the object candidate and computing points on the object from different views to form a feature vector at each computed point; a learning-feature graph-fingerprinting module configured to receive the local features and build a fingerprint of the object for tracking the object; and an object graph prototype module for receiving, storing, and transmitting object fingerprint information to the learning-feature graph-fingerprinting module to be updated as new features are received.
1. An active learning system for fingerprinting an object in an image frame, comprising: one or more processors that include: an oriented localized filter module being configured to extract local features from a potential object candidate within the image frame by receiving an object model of the object candidate and computing points on the object from different views to form a feature vector at each computed point; a learning-feature graph-fingerprinting module configured to receive the local features and build a fingerprint of the object for tracking the object; and an object graph prototype module for receiving, storing, and transmitting object fingerprint information to the learning-feature graph-fingerprinting module to be updated as new features are received. 2. An active learning system as set forth in claim 1 , further comprising: a flow-based object segmentation module for segmenting a potential object candidate from a sequence of video frames taken from a scene, and communicating the segmented potential object candidate to the oriented localized filter module for iconic feature extraction; and an incremental learning module for predicting a general class of the potential object candidate.