3D face recognition with wireless transportation

Show simple item record


dc.contributor Lu , Mi
dc.contributor Xiong , Zixiang
dc.creator Zou , Le
dc.date 2010 -01 -14T23 :59 :50Z
dc.date 2010 -01 -16T01 :47 :17Z
dc.date 2010 -01 -14T23 :59 :50Z
dc.date 2010 -01 -16T01 :47 :17Z
dc.date 2007 -08
dc.date 2009 -05 -15
dc.date.accessioned 2013 -03 -12T17 :54 :05Z
dc.date.available 2013 -03 -12T17 :54 :05Z
dc.date.issued 2013 -03 -12
dc.identifier http : / /hdl .handle .net /1969 .1 /ETD -TAMU -1448
dc.identifier.uri http : / /hdl .handle .net /1969 .1 /ETD -TAMU -1448
dc.description In this dissertation , we focus on two related parts of a 3D face recognition system with wireless transportation . In the first part , the core components of the system , namely , the feature extraction and classification component , are introduced . In the feature extraction component , range images are taken as inputs and processed in order to extract features . The classification component uses the extracted features as inputs and makes classification decisions based on trained classifiers . 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 classification components ) of the face recognition system . Contrary to the conventional definition of being a transducer , a sensor node can be a person , a vehicle , etc . The wireless transportation component not only brings flexibility to the system but also makes the “proactive” face recognition possible . For the feature extraction component , we first 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 differentiate facial images . For the classification component , a classifier based on Mahalanobis distance is introduced . Based on the classifier , recognition performances of the extracted features are given . The classification 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 efficient 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 .
dc.format electronic
dc.format application /pdf
dc.format born digital
dc.language en _US
dc.subject Face recognition
dc.subject Feature extraction
dc.subject Three -dimensional vision
dc.subject Digital Image Processing
dc.subject Image Classification
dc.subject 3D model
dc.subject Distributed algorithm
dc.subject Graph theory
dc.subject Protocols
dc.subject Routing
dc.subject Sensor networks
dc.subject Shortest path
dc.subject Topology
dc.title 3D face recognition with wireless transportation
dc.type Book
dc.type Thesis
dc.type Electronic Dissertation
dc.type text

Citation

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

Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Search DSpace

Advanced Search

Browse