3D face recognition with wireless transportation

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dc.contributor.advisor Lu , Mi en_US
dc.contributor.committeeMember Klappenecker , Andreas en_US
dc.creator Zou , Le en_US
dc.date.accessioned 2010 -01 -14T23 :59 :50Z
dc.date.accessioned 2014 -02 -19T19 :36 :45Z
dc.date.available 2010 -01 -14T23 :59 :50Z
dc.date.available 2014 -02 -19T19 :36 :45Z
dc.date.created 2007 -08 en_US
dc.date.issued 2009 -05 -15 en_US
dc.identifier.uri http : / /hdl .handle .net /1969 .1 /ETD -TAMU -1448
dc.description.abstract In this dissertation , we focus on two related parts of a 3D face recognition system with wireless transportation . In the ?rst part , the core components of the system , namely , the feature extraction and classi ?cation component , are introduced . In the feature extraction component , range images are taken as inputs and processed in order to extract features . The classi ?cation component uses the extracted features as inputs and makes classi ?cation decisions based on trained classi ?ers . In the second part , we consider the wireless transportation problem of range images , which are captured by scattered sensor nodes from target objects and are forwarded to the core components (i .e . , feature extraction and classi ?cation components ) of the face recognition system . Contrary to the conventional de ?nition of being a transducer , a sensor node can be a person , a vehicle , etc . The wireless transportation component not only brings ?exibility to the system but also makes the ?proactive ? face recognition possible . For the feature extraction component , we ?rst introduce the 3D Morphable Model . Then a 3D feature extraction algorithm based on the 3D Morphable Model is presented . The algorithm is insensitive to facial expression . Experimental results show that it can accurately extract features . Following that , we discuss the generic face warping algorithm that can quickly extract features with high accuracy . The proposed algorithm is robust to holes , facial expressions and hair . Furthermore , our experimental results show that the generated features can highly di ?erentiate facial images . For the classi ?cation component , a classi ?er based on Mahalanobis distance is introduced . Based on the classi ?er , recognition performances of the extracted features are given . The classi ?cation results demonstrate the advantage of the features from the generic face warping algorithm . For the wireless transportation of the captured images , we consider the location -based wireless sensor networks (WSN ) . In order to achieve e ?cient routing perfor ?mance , a set of distributed stateless routing protocols (PAGER ) are proposed for wireless sensor networks . The loop -free and delivery -guaranty properties of the static version (PAGER -S ) are proved . Then the performance of PAGER protocols are compared with other well -known routing schemes using network simulator 2 (NS2 ) . Simulation results demonstrate the advantages of PAGER . en_US
dc.format.medium electronic en_US
dc.format.mimetype application /pdf en_US
dc.language.iso en _US en_US
dc.subject Face recognition en_US
dc.title 3D face recognition with wireless transportation en_US
dc.type Book en
dc.type.genre Electronic Dissertation en_US
dc.type.material text en_US
dc.format.digitalOrigin born digital en_US

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3D face recognition with wireless transportation. Available electronically from http : / /hdl .handle .net /1969 .1 /ETD -TAMU -1448 .

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