This　paper　proposes　a　method　that　can　perform　human　motion　pattern　recognition　using　Principal　Component　Analysis　(PCA)　and　neural　network.　Moving　target　is　detected　from　a　set　of　video　image　sequences,　and　the　silhouette　is　extracted.　The　two-dimensional　signal　of　contour　is　converted　into　one-dimensional　signal　through　measuring　the　distance　of　pixels　between　centroid　and　boundaries　of　the　silhouette.　Feature　of　human　motion　is　extracted　by　PCA,　and　then　a　neural　network　is　employed　to　classify　the　motion　pattern　into　three　categories:　walking,　running,　and　other　motions.　Experimental　results　have　shown　that　this　method　is　capable　of　recognizing　the　motion　pattern　mentioned　above　effectively.　©　2005　IEEE.