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Sökning: onr:"swepub:oai:DiVA.org:kth-309072" > NeuroIV :

NeuroIV : Neuromorphic Vision Meets Intelligent Vehicle Towards Safe Driving With a New Database and Baseline Evaluations

Chen, Guang (författare)
Tongji Univ, Sch Automot Studies, Shanghai 200092, Peoples R China.;State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410012, Peoples R China.;Tech Univ Munich, Dept Informat, D-80333 Munich, Germany.
Wang, Fa (författare)
Tongji Univ, Sch Automot Studies, Shanghai 200092, Peoples R China.
Li, Weijun (författare)
Tongji Univ, Sch Automot Studies, Shanghai 200092, Peoples R China.
visa fler...
Hong, Lin (författare)
Shandong Univ Sci & Technol, Sch Transportat, Qingdao 266510, Peoples R China.
Conradt, Jörg (författare)
KTH,Beräkningsvetenskap och beräkningsteknik (CST)
Chen, Jieneng (författare)
Tongji Univ, Sch Automot Studies, Shanghai 200092, Peoples R China.
Zhang, Zhenyan (författare)
Tongji Univ, Sch Automot Studies, Shanghai 200092, Peoples R China.
Lu, Yiwen (författare)
Tongji Univ, Sch Automot Studies, Shanghai 200092, Peoples R China.
Knoll, Alois (författare)
Tech Univ Munich, Dept Informat, D-80333 Munich, Germany.
visa färre...
Tongji Univ, Sch Automot Studies, Shanghai 200092, Peoples R China;State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410012, Peoples R China.;Tech Univ Munich, Dept Informat, D-80333 Munich, Germany. Tongji Univ, Sch Automot Studies, Shanghai 200092, Peoples R China. (creator_code:org_t)
Institute of Electrical and Electronics Engineers (IEEE), 2022
2022
Engelska.
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1524-9050 .- 1558-0016. ; 23:2, s. 1171-1183
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Neuromorphic vision sensors such as the Dynamic and Active-pixel Vision Sensor (DAVIS) using silicon retina are inspired by biological vision, they generate streams of asynchronous events to indicate local log-intensity brightness changes. Their properties of high temporal resolution, low-bandwidth, lightweight computation, and low-latency make them a good fit for many applications of motion perception in the intelligent vehicle. However, as a younger and smaller research field compared to classical computer vision, neuromorphic vision is rarely connected with the intelligent vehicle. For this purpose, we present three novel datasets recorded with DAVIS sensors and depth sensor for the distracted driving research and focus on driver drowsiness detection, driver gaze-zone recognition, and driver hand-gesture recognition. To facilitate the comparison with classical computer vision, we record the RGB, depth and infrared data with a depth sensor simultaneously. The total volume of this dataset has 27360 samples. To unlock the potential of neuromorphic vision on the intelligent vehicle, we utilize three popular event-encoding methods to convert asynchronous event slices to event-frames and adapt state-of-the-art convolutional architectures to extensively evaluate their performances on this dataset. Together with qualitative and quantitative results, this work provides a new database and baseline evaluations named NeuroIV in cross-cutting areas of neuromorphic vision and intelligent vehicle.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)

Nyckelord

Neuromorphics
Vision sensors
Intelligent sensors
Intelligent vehicles
Cameras
Neuromorphic vision
distracted driving
advanced driver assistance system
database and baseline evaluations
event encoding
deep learning

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