Now showing items 1-6 of 6
The Individual is Nothing, the Class Everything: Psychophysics and Modeling of Recognition in Obect Classes
Most psychophysical studies of object recognition have focussed on the recognition and representation of individual objects subjects had previously explicitely been trained on. Correspondingly, modeling studies have often ...
People Recognition in Image Sequences by Supervised Learning
We describe a system that learns from examples to recognize people in images taken indoors. Images of people are represented by color-based and shape-based features. Recognition is carried out through combinations of Support ...
Feature Selection for Face Detection
We present a new method to select features for a face detection system using Support Vector Machines (SVMs). In the first step we reduce the dimensionality of the input space by projecting the data into a subset of ...
Learning-Based Approach to Estimation of Morphable Model Parameters
We describe the key role played by partial evaluation in the Supercomputing Toolkit, a parallel computing system for scientific applications that effectively exploits the vast amount of parallelism exposed by partial ...
Face Detection in Still Gray Images
We present a trainable system for detecting frontal and near-frontal views of faces in still gray images using Support Vector Machines (SVMs). We first consider the problem of detecting the whole face pattern by a single ...
Computational Models of Object Recognition in Cortex: A Review
Understanding how biological visual systems perform object recognition is one of the ultimate goals in computational neuroscience. Among the biological models of recognition the main distinctions are between feedforward ...