Despite active research and significant progress in the last 30 years, eye detection and
tracking remains challenging due to the individuality of eyes, occlusion, variability in scale …

We argue that the study of human vision should be aimed at determining how humans
perform natural tasks with natural images. Attempts to understand the phenomenology of …

In recent years, deep learning-based algorithms have brought great improvements to rigid
object detection. In addition to rigid objects, remote sensing images also contain many …

We describe an object detection system based on mixtures of multiscale deformable part
models. Our system is able to represent highly variable object classes and achieves state-of …

We describe a new hierarchical representation for two-dimensional objects that captures
shape information at multiple levels of resolution. This representation is based on a …

An active contour tracker is presented which can be used for gaze-based interaction with off-
the-shelf components. The underlying contour model is based on image statistics and …

Optimization is a powerful paradigm for expressing and solving problems in a wide range of
areas, and has been successfully applied to many vision problems. Discrete optimization …

We describe some techniques that can be used to represent and detect deformable shapes
in images. The main difficulty with deformable template models is the very large or infinite …

This study develops filtered two-fluid model (fTFM) closures by coupling computational fluid
dynamics (CFD) and deep learning algorithm (DL) for enabling coarse-grid simulations at …

Finding a template in a search image is one of the core problems in many computer vision
applications, such as template matching, image semantic alignment, image-to-GPS …