DocumentCode
1768197
Title
An Embedded Vision Engine (EVE) for automotive vision processing
Author
Mandal, Dipan Kumar ; Sankaran, Jagadeesh ; Gupta, Arpan ; Castille, Kyle ; Gondkar, Shraddha ; Kamath, Sanmati ; Sundar, Pooja ; Phipps, Alan
Author_Institution
Texas Instrum., Bangalore, India
fYear
2014
fDate
1-5 June 2014
Firstpage
49
Lastpage
52
Abstract
This paper introduces Embedded Vision Engine (EVE) - a fully programmable, specialized vector processor architecture aimed at solving challenging Computer Vision applications encountered in Advanced Driver Assistance Systems (ADAS). The paper outlines the complexity of automotive vision applications, establishes why specialized architecture (like EVE) is needed and outlines the EVE architecture, its components and programming model. We present comparative benchmarks and provide an overview of many carefully crafted features of EVE for power management, inter processor communication, functional safety and software debug that helps in building a scalable, area-power efficient System-on-Chip (SoC) solutions for the cost, power and safety sensitive automotive vision space.
Keywords
computer vision; system-on-chip; traffic engineering computing; ADAS; EVE architecture; advanced driver assistance system; area-power efficient SoC; automotive vision processing; computer vision; embedded vision engine; functional safety; interprocessor communication; power management; software debug; system-on-chip; vector processor architecture; Automotive engineering; Buffer storage; Computer architecture; Digital signal processing; Engines; Safety; Vectors; ADAS; Automotive Vision; Computer Vision; Processor Architecture; SIMD processor; Vector Processor;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems (ISCAS), 2014 IEEE International Symposium on
Conference_Location
Melbourne VIC
Print_ISBN
978-1-4799-3431-7
Type
conf
DOI
10.1109/ISCAS.2014.6865062
Filename
6865062
Link To Document