▁by ▁changes ▁in ▁light ing ▁or ▁pose , ▁ 3 D ▁face ▁recognition ▁has ▁the ▁potential ▁to ▁improve ▁performance ▁under ▁these ▁conditions . ▁ ▁In ▁the ▁last ▁couple ▁years ▁there ▁have ▁been ▁adv ances ▁in ▁computer ▁graphics ▁and ▁computer ▁vision ▁on ▁model ing ▁light ing ▁and ▁pose ▁changes ▁in ▁fa cial ▁imag ery . ▁These ▁adv ances ▁have ▁led ▁to ▁the ▁development ▁of ▁new ▁computer ▁algorithms ▁that ▁can ▁automatically ▁correct ▁for ▁light ing ▁and ▁pose ▁changes ▁in ▁fa cial ▁imag ery . ▁These ▁new ▁algorithms ▁work ▁by ▁pre processing ▁a ▁fa cial ▁image ▁to ▁correct ▁for ▁light ing ▁and ▁pose ▁prior ▁to ▁being ▁processed ▁through ▁a ▁face ▁recognition ▁system . ▁The ▁pre processing ▁portion ▁of ▁the ▁FR GC ▁will ▁measure ▁the ▁impact ▁of ▁new ▁pre processing ▁algorithms ▁on ▁recognition ▁performance . ▁ ▁The ▁FR GC ▁improved ▁the ▁capabilities ▁of ▁automatic ▁face ▁recognition ▁systems ▁through ▁experiment ation ▁with ▁clearly ▁stated ▁goals ▁and ▁challenge ▁problems . ▁Research ers ▁and ▁developers ▁can ▁develop ▁new ▁algorithms ▁and ▁systems ▁that ▁meet ▁the ▁FR GC ▁goals . ▁The ▁development ▁of ▁the ▁new ▁algorithms ▁and ▁systems ▁is ▁facil itated ▁by ▁the ▁FR GC ▁challenge ▁problems . ▁ ▁Str ucture ▁of ▁the ▁Face ▁Rec ogn ition ▁Grand ▁Challenge ▁The ▁FR GC ▁is ▁struct ured ▁around ▁challenge ▁problems ▁that ▁are ▁designed ▁to ▁challenge ▁research ers ▁to ▁meet ▁the ▁FR GC ▁performance ▁goal . ▁ ▁There ▁are ▁three ▁aspects ▁of ▁the ▁FR GC ▁that ▁will ▁be ▁new ▁to ▁the ▁face ▁recognition ▁community . ▁The ▁first ▁aspect ▁is ▁the ▁size ▁of ▁the ▁FR GC