Martial　arts　tracking　is　an　important　research　topic　in　computer　vision　and　artificial　intelligence.　It　has　extensive　and　vital　applications　in　video　monitoring,　interactive　animation　and　3D　simulation,　motion　capture,　and　advanced　human-computer　interaction.　However,　due　to　the　change　of　martial　arts＇　body　posture,　clothing　variability,　and　light　mixing,　the　appearance　changes　significantly.　As　a　result,　accurate　posture　tracking　becomes　a　complicated　problem.　A　solution　to　this　complicated　problem　is　studied　in　this　paper.　The　proposed　solution　improves　the　accuracy　of　martial　arts　tracking　by　the　image　representation　method　of　martial　arts　tracking.　This　method　is　based　on　the　second-generation　strip　wave　transform　and　applies　it　to　the　video　martial　arts　tracking　based　on　the　machine　learning　method.　©　2021　Jing　Li　and　Guangren　Zhou.