Haar-Like feature implementation on FPGAs for Advanced Driver-Assistant Systems

Blanco Garrido, Cristina and Mariño Andrés, Rodrigo and Lanza-Gutiérrez, José Manuel and Riesgo Alcaide, Teresa (2018). Haar-Like feature implementation on FPGAs for Advanced Driver-Assistant Systems. In: "DCIS 2017: XXXII Conference on Design of Circuits and Integrated Systems", 14th-16th November 2018, Lyon, France. ISBN 978-1-7281-0171-2. pp. 1-8.

Description

Title: Haar-Like feature implementation on FPGAs for Advanced Driver-Assistant Systems
Author/s:
  • Blanco Garrido, Cristina
  • Mariño Andrés, Rodrigo
  • Lanza-Gutiérrez, José Manuel
  • Riesgo Alcaide, Teresa
Item Type: Presentation at Congress or Conference (Article)
Event Title: DCIS 2017: XXXII Conference on Design of Circuits and Integrated Systems
Event Dates: 14th-16th November 2018
Event Location: Lyon, France
Title of Book: Proceedings DCIS 2017: XXXII Conference on Design of Circuits and Integrated Systems
Date: 2018
ISBN: 978-1-7281-0171-2
Subjects:
Freetext Keywords: Haar-like Feature Extraction; Expert Sensors; camera-based sensor; Machine Learning; FPSoC
Faculty: E.T.S.I. Industriales (UPM)
Department: Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Nowadays, there is a growing trend in developing advanced computational techniques for Advanced DriverAssistant Systems (ADAS) using low-cost devices. One of the relevant ADAS application is vehicle detection based on camera sensors. The state-of-the-art approaches for this application utilize machine learning techniques. These techniques might be divided into feature extraction and inference algorithms. Feature extraction requires high computational capabilities and execution time because it extracts the most relevant data from a camera frame. From the embedded system point of view, lowcost heterogeneous systems based on FPGAs might provide a framework to develop feature extraction techniques. According to vehicle detection, haar-like is one of the most used feature extraction technique in the literature. As a result, this paper proposes a haar-like feature extraction architecture in hardware for achieving real-time requirements in the automobile industry, analyzing parameters as resource utilization and system latency.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTEC2017-86722-C4-2-RPLATINOUnspecifiedPLATAFORMA HW/SW DISTRIBUIDA PARA EL PROCESAMIENTO INTELIGENTE DE INFORMACION SENSORIAL HETEROGENEA EN APLICACIONES DE SUPERVISION DE GRANDES ESPACIOS NATURALES
Government of SpainTEC2014-58036-C4-2-RREBECCAUnspecifiedSISTEMAS ELECTRONICOS EMPOTRADOS CONFIABLES PARA CONTROL DE CIUDADES BAJO SITUACIONES ATIPICAS

More information

Item ID: 55162
DC Identifier: http://oa.upm.es/55162/
OAI Identifier: oai:oa.upm.es:55162
Official URL: https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8679952
Deposited by: Memoria Investigacion
Deposited on: 05 Jun 2019 15:04
Last Modified: 05 Jun 2019 15:04
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