Yuri Ivanov - Arlington MA, US Pavan Turaga - Greenbelt MD, US
International Classification:
H04N 7/18 G06N 5/02
US Classification:
348143, 706 54, 706 11, 348E07085
Abstract:
A system and a method for detecting events in time-series data are disclosed, wherein the time-series data represent atomic activities sensed by sensors in an environment, and wherein each atomic activity includes a time and a location at which the each atomic activity is sensed, comprising the steps of: mapping a specified event to a Petri net (PN), wherein the specified event is a spatio-temporal pattern of the atomic activities, wherein the spatio-temporal pattern is based only on the time and the location of the atomic activities, such that a spatio-temporal sequence of the atomic activities forms a primitive activity, and the spatio-temporal pattern includes primitive activities and constraints on the primitive activities, wherein the constraints are sequential and/or concurrent; and detecting, in the time-series data, a sensed event corresponding the specified event mapped to the PN to produce a result, wherein the detecting is performed by a processor.
Adaptive Video Subsampling For Energy Efficient Object Detection
Andreas Spanias - Tempe AZ, US Pavan Turaga - Tempe AZ, US Sameeksha Katoch - Tempe AZ, US Suren Jayasuriya - Tempe AZ, US Divya Mohan - Belmont CA, US
Assignee:
Arizona Board of Regents on Behalf of Arizona State University - Tempe AZ
International Classification:
G06T 5/40 G06T 5/50 G06T 7/00
Abstract:
Various embodiments of systems and methods for adaptive video subsampling for energy-efficient object detection are disclosed herein.
Systems And Methods For Skyline Prediction For Cyber-Physical Photovoltaic Array Control
Henry Braun - Tempe AZ, US Pavan Turaga - Chandler AZ, US Andreas Spanias - Tempe AZ, US Cihan Tepedelenlioglu - Chandler AZ, US
Assignee:
ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY - Scottsdale AZ
International Classification:
G06K 9/62 G06N 3/08
Abstract:
The disclosure relates to an image recognition algorithm implemented by a hardware control system which operates directly on data from a compressed sensing camera. A computationally expensive image reconstruction step can be avoided, allowing faster operation and reducing the computing requirements of the system. The method may implement an algorithm that can operate at speeds comparable to an equivalent approach operating on a conventional camera's output. In addition, at high compression ratios, the algorithm can outperform approaches in which an image is first reconstructed and then classified.