This paper describes a PC-based vision system that can be used to detect moving objects from a mobile robot. An image processing board equipped with an MPEG motion estimation processor calculates a sparse but robust optic flow in real-time. An algorithm to
Figure7.Segmentationresults(PAL, rst eldonly)
ofthoseboundingboxesinalist,hypothesesofobjectre-gionscanalsobemaintainedwhenthedetectionfailsforashorttime,i.e.whenamovingobjecttemporarilystops.Fig.7showssamplesfromatypicalimagesequenceusedintheexperiments.Thecamera(i.e.therobot)ismov-ingalongaslightleftturnwhileapersoncrossesthescene.Vectorsnotbelongingtothebackgroundarerobustlyde-tectedandclustered.Theboundingboxescan,ofcourse,onlyencompassthosepartsofthemovingobjectswhereoptic owvectorshavebeencalculatedandhavepassedthesiftingprocess.
4Conclusionandfurtherwork
Wehavepresentedalowcostbutef cientimagepro-cessingsystemthatisabletocalculateasparseoptic owinreal-time(upto525vectorsperframe).Further,aprac-ticalalgorithmtodetectmovingobjectsbysegmentationofthe ow eldwasproposedandsomeexperimentalresultswerepresented.Thesystemiscurrentlyusedinclosedloopexperimentsonanautonomous,vision-guidedrobot.
Furtherworkwillbeconcernedwithimprovementstotherobustnessofthesystem.ApplyingKalman lteringtotheestimationofthecamerarotationcanfurtherreducethesensitivitytonoiseandallowapredictionofevenwhenthebackgrounddetectiontemporarilyfails.Forthevectorsbelongingtothebackground,theadditionalparameter