University of California

About: University of California is a education organization based out in Oakland, California, United States. It is known for research contribution in the topics: Population & Layer (electronics). The organization has 55175 authors who have published 52933 publications receiving 1491169 citations. The organization is also known as: UC & University of California System.

Digital processing of video images

Abstract: Digital video imaging systems and techniques for efficiently transforming warped video images into rectilinear video images, real-time tracking of persons and objects, face recognition of persons, monitoring and tracking head pose of a person and associated perspective view of the person.

Body monitoring and imaging apparatus and method

Abstract: A non-acoustic pulse-echo radar monitor is employed in the repetitive mode, whereby a large number of reflected pulses are averaged to produce a voltage that modulates an audio oscillator to produce a tone that corresponds to the heart motion. The antenna used in this monitor generally comprises two flat copper foils, thus permitting the antenna to be housed in a substantially flat housing. The monitor converts the detected voltage to an audible signal with both amplitude modulation and Doppler effect. It further uses a dual time constant to reduce the effect of gross sensor-to-surface movement. The monitor detects the movement of one or more internal body parts, such as the heart, lungs, arteries, and vocal chords, and includes a pulse generator for simultaneously inputting a sequence of pulses to a transmit path and a gating path. The pulses transmitted along the transmit path drive an impulse generator and provide corresponding transmit pulses that are applied to a transmit antenna. The gating path includes a range delay generator which generates timed gating pulses. The timed gating pulses cause the receive path to selectively conduct pulses reflected from the body parts and received by a receive antenna. The monitor output potential can be separated into a cardiac output indicative of the physical movement of the heart, and a pulmonary output indicative of the physical movement of the lung.

People Manipulate Objects (but Cultivate Fields): Beyond the Raster-Vector Debate in GIS

Abstract: The ongoing debate in GIS regarding the relative merits of vector versus raster representations of spatial information is usually couched in technical terms Yet the technical question of the most appropriate data structure begs the philosophical question of the most appropriate conceptualization of geographic space The paper confronts this latter question in the context of the opposition between the “object” and “field” views of space I suggest that GIS can turn a rather dry debate into a source of insights regarding the nature of its subject matter by learning from how people actually experience and deal with the geographic world Human cognition indeed appears to make use of both the object and field views, but at different geographic scales, and for different purposes These observations suggest a list of desiderata for the next round of thinking about spatial representation in GIS

Hierarchical Surface Prediction for 3D Object Reconstruction

Abstract: Recently, Convolutional Neural Networks have shown promising results for 3D geometry prediction. They can make predictions from very little input data such as a single color image. A major limitation of such approaches is that they only predict a coarse resolution voxel grid, which does not capture the surface of the objects well. We propose a general framework, called hierarchical surface prediction (HSP), which facilitates prediction of high resolution voxel grids. The main insight is that it is sufficient to predict high resolution voxels around the predicted surfaces. The exterior and interior of the objects can be represented with coarse resolution voxels. Our approach is not dependent on a specific input type. We show results for geometry prediction from color images, depth images and shape completion from partial voxel grids. Our analysis shows that our high resolution predictions are more accurate than low resolution predictions.

Knowledge representation in fuzzy logic

Abstract: The conventional approaches to knowledge representation, e.g., semantic networks, frames, predicate calculus and Prolog, are based on bivalent logic. A serious shortcoming of such approaches is their inability to come to grips with the issue of uncertainty and imprecision. As a consequence, the conventional approaches do not provide an adequate model for modes of reasoning which are approximate rather than exact. Most modes of human reasoning and all of commonsense reasoning fall into this category.