Feature based driver's Distraction Detection Techniques using Neural Network based on Fixed Single Camera

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dc.contributor.authorKhawaja Ubaid Ur Rehman
dc.contributor.authorMuhammad Maaz Aslam
dc.contributor.authorMuhammad Hassan Raza
dc.contributor.authorAyesha Farooq
dc.date.accessioned2016-03-29T08:46:43Z
dc.date.available2016-03-29T08:46:43Z
dc.date.issued2015
dc.descriptionSupervisor: Syed Farooq Alien_US
dc.description.abstractMost accidents occur due to drowsiness while driving, avoiding road signs and due to driver's distraction. Driver's distraction depends on various factors which includes talking with passengers while driving, avoiding road signs, mood disorder, nervousness, anger, over-excitement, anxiety, loud music, illness and fatigue that may result in the distraction of a driver. This paper introduces novel approaches that compute various features using the facial points especially features computed using motion vectors and interpolation. These facial points are detected by Active Shape Model (ASM) and Boosted Regression with Markov Networks (BoRMaN). The features of different frames are trained and tested on Neural Networks (NN) to decide about driver's distraction. These approaches are also scale invariant. The result shows that the approach 4 using novel idea of motion vectors and interpolation techniques outperforms all other approaches.en_US
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/1637
dc.publisherUNIVERSITY OF MANAGEMENT AND TECHNOLOGYen_US
dc.subjectBS Thesisen_US
dc.subjectDriver's Distractionen_US
dc.subjectDetection Techniquesen_US
dc.subjectNeural Networken_US
dc.titleFeature based driver's Distraction Detection Techniques using Neural Network based on Fixed Single Cameraen_US
dc.titleFeature based driver's distraction detection techniques using neural network based on fixed single cameraen_us
dc.typeThesisen_US
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