ARGUS: An Automated Multi-Agent Visitor Identi cation System

نویسندگان

  • Rahul Sukthankar
  • Robert G. Stockton
چکیده

ARGUS is a multi-agent visitor identi cation system distributed over several workstations. Human faces are extracted from security camera images by a neuralnetwork-based face detector, and identi ed as frequent visitors by ARENA, a memory-based face recognition system. ARGUS then uses a messaging system to notify hosts that their guests have arrived. An interface agent enables users to submit feedback, which is immediately incorporated by ARENA to improve its face recognition performance. The ARGUS components were rapidly developed using JGram, an agent framework that is also detailed in this paper. JGram automatically converts high-level agent speci cations into Java source code, and assembles complex tasks by composing individual agent services into a JGram pipeline. ARGUS has been operating successfully in an outdoor environment for several months.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

ARGUS: An Automated Multi-Agent Visitor Identification System

ARGUS is a multi-agent visitor identification system distributed over several workstations. Human faces are extracted from security camera images by a neuralnetwork-based face detector, and identified as frequent visitors by ARENA, a memory-based face recognition system. ARGUS then uses a messaging system to notify hosts that their guests have arrived. An interface agent enables users to submit...

متن کامل

JGram: Rapid Development of Multi-Agent Pipelines for Real-World Tasks

Many real-world tasks can be decomposed into pipelines of sequential operations (where subtasks may themselves be composed of one or more pipelines). JGram is a framework enabling rapid development of such multi-agent systems. Each agent’s services are specified in the JGram Description Language (JDL), and automatically converted into Java source templates. These services may be invoked synchro...

متن کامل

SECURING INTERPRETABILITY OF FUZZY MODELS FOR MODELING NONLINEAR MIMO SYSTEMS USING A HYBRID OF EVOLUTIONARY ALGORITHMS

In this study, a Multi-Objective Genetic Algorithm (MOGA) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear Multi-input Multi-output (MIMO) systems. In the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. Furthermore, se- curing low-level and high-level ...

متن کامل

Reducing Retrieval Time in Automated Storage and Retrieval System with a Gravitational Conveyor Based on Multi-Agent Systems

The main objective of this study is to reduce the retrieval time of a list of products by choosing the best combination of storage and retrieval rules at any time. This is why we start by implementing some storage rules in an Automated Storage/Retrieval System (Automated Storage and Retrieval System: AS/RS) fitted with a gravity conveyor while some of these rules are dedicated to storage and ot...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1999