We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...
Background: As the canonical code is not universal, different theories about its origin and organization have appeared. The optimization or level of adaptation of the canonical ge...
We present a method for unsupervised topic modelling which adapts methods used in document classification (Blei et al., 2003; Griffiths and Steyvers, 2004) to unsegmented multi-pa...
We propose to utilize micro features, namely facial marks (e.g., freckles, moles, and scars) to improve face recognition and retrieval performance. Facial marks can be used in thr...
We present automated, real-time models built with machine learning algorithms which use videotapes of subjects' faces in conjunction with physiological measurements to predic...
Jeremy N. Bailenson, Emmanuel D. Pontikakis, Iris ...