The aim of this paper is to present a novel method for processing a digitized image that will allow pertinent information to be extracted on object movement in a scene. A frame difference method locates the moving candidates in a region which is evaluated by a hypothesis testing procedure to identify accretion and deletion regions. Accretion regions are selected and used as seeds to search for moving objects in the current frame. Contour tracing is applied to establish the boundary of an accretion region which is then used to help recognize the moving object. The results of this work reveal that motion can be used as an effective cue for object detection from an image sequence.
References
1.
NagelH. H.Formation of an object concept by analysis of systematic time variations in the optically perceptible environment. Computer Graphics and Image Processing, 1978, 149–194.
2.
BarnardS. T.ThompsonW. B.Disparity analysis of images. IEEE Trans. on PAMI, 1980, 2, 333–340.
MoravecH. P.Visual mapping by a robot rover. IJCAI, 1979, 598–600.
5.
ThompsonW. B.Combining motion and contrast for segmentations. IEEE Trans. on PAMI, 1980, 2(6), 543–549.
6.
PotterK.Velocity as a cue to segmentation. IEEE Trans. on SMC, 1975, 390–394.
7.
JainR.MilitzerD.NagelH.-H.Separating non-stationary scene components in a sequence of real world TV images. 5th IJCAI, 1977, 612–618.
8.
JainR.NagelH.-H.On a motion analysis of accumulative difference picture from image sequences of real world scenes. IEEE Trans. on PAMI, 1979, 1(2), 206–214.
9.
CowartA. E.SynderW. E.RuedgerW.The detection of unresolved targets using the Hough transform. Computer Vision Graphs and Image Processing, 1983, 21, 222–238.
10.
KaplanG. A.Kinetic disruption of optical texture: the perception of depth at an edge. Perception and Psychophysics, 1969, 6, 193–198.
11.
MutchK. M.ThompsonW. B.Analysis of accretion and deletion at boundaries in dynamic scenes. IEEE Trans. on PAMI, 1985, 7(2), 133–138.
12.
TsaoH.A novel approach to multiple nonuniform moving target detection and tracking. Institute of Computer Engineering, National Chaio Tung University, Taiwan, 1981.
13.
KellyM. D.Edge detection in picture by computer using planning. Machine intelligence VI (Ed. MeltzerB.), 1971, pp. 397–409 (Edinburgh University Press, Edinburgh).
14.
MinskyM.Step toward artificial intelligence. In Computers and thought (Eds FeigenbaumE.FeldmanJ.), 1963, pp. 406–450 (McGraw-Hill, Maidenhead, Berks).
15.
PriceK.ReddyR.Change detection and analysis in multispectral images. IJCAI, 1977, 619–625.
16.
LinC. S.Statistics for psychology and eduction, 1975 (Tonhwa Book Co.).
17.
JainR.NagelH. J.On the analysis of accumulative difference picture from image sequences of real world scenes. IEEE Trans. on PAMI, 1979, 1(2), 206–214.
18.
JainR.MartinW. N.AggarwalJ. K.Segmentation through the detection of changes due to motion. Computer Graphics and Image Processing, 1979, 11, 13–34.
