Motion video analysis using planar parallax
Harpreet S. Sawhney
IS&T/SPIE Electronic Imaging 1994
Solving real-world classification and recognition problems requires a principled way of modeling the physical phenomena generating the observed data and the uncertainty in it. The uncertainty originates from the fact that many data generation aspects are influenced by nondirectly measurable variables or are too complex to model and hence are treated as random fluctuations. For example, in speech production, uncertainty could arise from vocal tract variations among different people or corruption by noise. The goal of modeling is to establish a generalization from the set of observed data such that accurate inference (classification, decision, recognition) can be made about the data yet to be observed, which we refer to as unseen data. © 2012 IEEE.
Harpreet S. Sawhney
IS&T/SPIE Electronic Imaging 1994
Hang-Yip Liu, Steffen Schulze, et al.
Proceedings of SPIE - The International Society for Optical Engineering
I.K. Pour, D.J. Krajnovich, et al.
SPIE Optical Materials for High Average Power Lasers 1992
Ziv Bar-Yossef, T.S. Jayram, et al.
Journal of Computer and System Sciences