Recognizing people at a distance is challenging from various considerations, including sensing, robust processing
algorithms, changing environmental conditions and fusing multiple modalities. This paper considers face, side face, gait
and ear and their possible fusion for human recognition. It presents an overview of some of the techniques that we have
developed for (a) super-resolution-based face recognition in video, (b) gait-based recognition in video, (c) fusion of
super-resolved side face and gait in video, (d) ear recognition in color/range images, and (e) fusion performance
prediction and validation. It presents various real-world examples to illustrate the ideas and points out the relative merits
of the approaches that are discussed.