IS = { zkontrolovano 13 Jan 2005 },
  UPDATE  = { 2004-05-31 },
  author =      {{\v S}ochman, Jan and Matas, Ji{\v r}{\'\i}},
  title =       {{AdaBoost} with Totally Corrective Updates for Fast 
                 Face Detection},
  year =        {2004},
  pages =       {445--450},
  booktitle =   {FGR '04: Proceeding of the Sixth IEEE International
                 Conference on Automatic Face and Gesture Recognition},
  editor =      {Deeber Azada},
  publisher =   {IEEE Computer Society},
  address =     {10662 Los Vaqueros Circle, P.O.Box 3014, Los Alamitos, USA},
  isbn =        {0-7695-2122-3},
  book_pages =  {904},
  month =       {May},
  day =         {17--19},
  venue =       {Center for Artificial Vision Research, 
                 Korea University, Jamsil Hotel, Seoul, Korea South},
  organization ={IEEE Computer Society; Korea Information Science
    Society; Korea Science and Engineering Foundation; Ministry of
    Information and Communication, Korea; US Air Force Office of
    Scientific Research; WatchVision, Inc.},
  annote = {An extension of the AdaBoost learning algorithm is
    proposed and brought to bear on the face detection problem. In
    each weak classifier selection cycle, the novel totally corrective
    algorithm reduces aggressively the upper bound on the training
    error by correcting coefficients of all weak classifiers. The
    correction steps are proven to lower the upper bound on the error
    without increasing computational complexity of the resulting
    detector. We show experimentally that for the face detection
    problem, where large training sets are available, the technique
    does not overfit.
      A cascaded face detector of the Viola-Jones type is built using
    AdaBoost with the Totally Corrective Update. The same detection
    and false positive rates are achieved with a detector that is
    20 perc. faster and consists of only a quarter of the weak
    classifiers needed for a classifier trained by standard
    AdaBoost. The latter property facilitates hardware implementation,
    the former opens scope for the increase in the search space,
    e.g. the range of scales at which faces are sought.},
  keywords =    {AdaBoost, face detection, computer vision},
  authorship =  {50-50},
  project =     {GACR 102/02/1539, CTU 0307313, MSMT Kontakt ME 678},
psurl       = {PDF },