Brad Bishop Seth Hutchinson Mark Spong Coordinated Science Lab Elect. and Comp. Eng. Coordinated Science Lab University of Illinois University of Illinois University of Illinois Urbana, IL 61801 Urbana, IL 61801 Urbana, IL 61801 Abstract In this paper we discuss the use of computer vision for real{time state estimation in feedback control systems. To this end, we construct a system for visual s...

This study aims to develop a prediction model evaluate the visual environment based on system. In this paper, in order systematically investigate characteristics field of discomfort glare, it was reported relationship between borderline comfort and discomfort1) (BCD) luminance experimental variables which background luminance, solid angle eccentric angle. Furthermore, relationship, characterist...

ABSTRACT In this paper we define edNCE random graph grammar and also generate the language for folded cube. Our purpose is to deal with the parameter and hypothesis testing on the equality of two binomial distribution population with missing data in language from edNCE random graph grammar. In addition consistency and its limiting distribution are obtained. KEYWORDS— Graph grammar, missing data...

This paper compares the influence a video self-avatar and a lack of a visual representation of a body have on height estimation when standing at a virtual visual cliff. A height estimation experiment was conducted using a custom augmented reality Oculus Rift hardware and software prototype also described in this paper. The results show a consistency with previous research demonstrating that the...

The use of computer vision based methods to explore the surrounding environment and track individuals, is further enhanced by the ability to move the visual system, a process realized by biological organisms. However, several perceptual issues arise from the rapid movement of the image acquisition system: blurred images and visual-proprioceptive transient delays result in incorrect spatial loca...

Abstruct-Zstimating the three-dimensional motion of an object from a sequence of projections is of paramount importance in a variety of applications in control and robotics, such as autonomous navigation, manipulation, servo, tracking, docking, planning, and surveillance. Although “visual motion estimation” is an old problem (the first formulations date back to the beginning of the century), on...

We present an unsupervised technique for visual learning, which is based on density estimation in high-dimensional spaces using an eigenspace decomposition. Two types of density estimates are derived for modeling the training data: a multivariate Gaussian (for unimodal distributions) and a Mixture-of-Gaussians model (for multimodal distributions). These probability densities are then used to fo...

In this paper a robust method for visual motion estimation under ego{motion is developed. The possible application of this method is image sequence analysis of road tra c or airport runway/taxiway scenes, where the camera is located in a moving vehicle. The method combines an application independent estimation of visual motion with speci c methods for instantaneous detection of the vanishing po...

Egocentric vision technology consists in capturing the actions of persons from their own visual point of view using wearable camera sensors. We apply this new paradigm to instrumental activities monitoring with the objective of providing new tools for the clinical evaluation of the impact of the disease on persons with dementia. In this paper, we introduce the current state of the development o...