system’s  components,  supporting  theoretical   ideas that  are  provided  by  a  Gaussian  pyramid, whereas by   experimental   results。   Section   2   introduces   a our framework also utilizes intermediate levels。 Also, frame-differencing technique   used   to   satisfy   the real-time   execution    would   require   that   a    high- goal  of visually  detecting  objects of interest。 Special performance   image   processor   (like  the   VLSI chip effort  is made  to develop algorithms  that  allow  the developed by van der Wal and Burt'') be available   to system to function with a consideration for real-time compute the pyramids。 constraints。   Section   3   addresses   additional   chal- The frame-differencing system by Dinstein'' lenges  that  an  automated   detection   and   tracking provides   an   interesting   alternative   to   the  figure system  must  often  consider,  including   analysis   of segmentation  approach  described  as  a  part  of  our visual   detection   results。   Section   4   presents    the framework。 Dinstein uses four projections to identify various  visual  calculations that  are used  in order to the  centers  of multiple  moving  objects  in  a fashion derive  the  dtsplacements   of  objects  or  significant that  is  only  slightly  less  robust  than  our   method。 features within objects。 Through these equations, the However, his method locates objects by majority vote system is able to follow the location of objects as they (much   like   Hough   transforms);   as   a   result,   the move。 Section 5 describes the hardware modules that method   does   not   provide   statistics   required   by are  required   to   operate   the  visual   detection and other   portions   of   our   framework   (e。g。   it cannot tracking   framework。   Section   6   demonstrates  the determine the geometric characteristics of    an framework’s  use  in  robotic  visual  serx oing。   Addi- identified  object)。 机器视觉维护检测与跟踪系统英文文献和中文翻译(4):http://www.youerw.com/fanyi/lunwen_81704.html