In　recent　years,　surgical　instrument　tracking　has　gained　significant　attention　in　the　field　of　surgical　navigation.　An　often-overlooked　problem　lies　in　the　instrument’s　irregular　movement　conflicting　with　the　tracking　system’s　fixed　viewpoint,　leading　to　line-of-sight　occlusion,　marker　occlusion,　and　sub-optimal　accuracy.　The　active　vision　tracking　system　(which　actively　adjusts　the　camera　viewpoint)　is　applied　to　address　this　issue.　In　this　paper,　two　algorithms　of　multi-view　fusion　and　dynamic　calibration　are　proposed　in　multi-camera　active　vision　to　allow　each　camera　to　adjust　its　viewpoint　independently.　These　algorithms　are　integrated　into　the　parallel　computing　of　the　frontend　and　backend　to　implement　the　positioning　of　the　instrument　from　multiple　perspectives　and　real-time　calibration　of　multiple　cameras.　Simulations　and　experiments　are　carried　out　to　test　the　accuracy　and　robustness　of　the　proposed　tracking　system.　Results　reveal　that　our　system　achieves　a　closer　trajectory　(0.12　mm)　to　the　ground　truth　compared　to　a　stereo　camera　tracking　system　(0.32　mm).　The　proposed　tracking　system　can　keep　track　of　the　instruments　within　the　positioning　volume　at　different　surgical　phases,　ensuring　consistent　navigation　and　improving　positioning　stability　and　accuracy.　©　2024　IOP　Publishing　Ltd.　All　rights,　including　for　text　and　data　mining,　AI　training,　and　similar　technologies,　are　reserved.