The　presented　research　addressed　a　novel　visual　attention　model　and　watershed　segmentation　based　approach　of　Regions　of　Interest　(ROIs)　extraction,　which　automatically　extracts　ROIs　and　copes　with　the　watershed　over-segmentation.　This　approach　uses　visual　attention　model　to　locate　salient　points,　in　which　the　winner　point,　the　most　salient　point,　is　selected　as　the　seed　point　of　watershed　segmentation.　ROIs　are　extracted　by　combining　salient　regions　with　watershed　segmented　regions.　The　focus　of　attention　(FOA)　is　shifted　to　measure　the　importance　or　interest　of　the　extracted　regions.　The　experimental　results　show　that　the　proposed　method　is　effective　to　reduce　over-segmentation　in　auto-extracting　ROIs　and　performs　well　for　different　objects.