1. A method for tracking an object using a sensor network comprising: selecting one or multiple reference frames from a plurality of data frames captured from the sensor network; identifying the object to track and obtaining a plurality of tracking target templates from the reference frames; extracting a set of multiple views from each of the tracking target templates; sampling a plurality of image patches proximate the location of the object in subsequent frames relative to the reference frame; extracting the set of multiple views from each image patch; solving a minimization problem in a robust multi-view multi-task framework for each image patch to calculate a probability for each of the multiple views; calculating an entropy of each of the multiple views using the probabilities of all the image patches; and determining a tracking result using the image patch with the highest probability using a multi-view weighting for the purpose of tracking and identifying the object.