Computer vision zero shot recognition

In this computer vision assignment, you will implement a zero-shot recognition system which resembles the system proposed in Christoph Lampert et al.'s [1] paper. (You don't need to read the paper to do this coursework.) All you need to know about this system is that it models the probability of a certain object (e.g. polar bear) being present in the image using the probabilities of being present for each of the attributes that a bear is known to have. For example, if we detect the attributes \white", \furry", \bulbous", \not lean", \not brown" etc. in the image, i.e. attributes that a polar bear is known to have, we can be fairly condent that there is a bear in the image. Hence, we can recognize a polar bear without ever having seen a polar bear, if (1) we know what attributes a polar bear has, and (2) we have classiers trained for these attributes, using images from other object classes (i.e. other animals).