Sport is a competitive field, where it is an element of measurement for a countries development. Due to this reason, sport analysis has become one of the major contribution in analysing and improving the performance level of an athlete. Video-based modality has become a crucial tool used in sport analysis by coaches and performance analysis. There were wide variety of techniques used in sport video analysis. The main purpose of this review paper is to compare and update review between traditional handcrafted approach and deep learning approach in sport video analysis based on human activity recognition, overview of recent study in video based human activity recognition in sport analysis and finally concluded with future potential direction in sport video analysis.

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A series of bio-based photocrosslinked polyester membranes, poly(1,8-octanediol-itaconate-citrate-dodecandioate), (POSCI) were synthesized through polycondensation followed by photocrosslinking under UV irradiation in the presence of 2,2-dimethoxy-2-phenylacetophenone (DMPA) as photoinitiator (PI). Upon varied UV exposure time and DMPA content, the corresponding changes in chemical, structural, and mechanical properties of the polymer were studied. The transmission peak of FTIR spectrum centred at 1725 cm-1 indicates the formation of ester structure. Contact angle results suggested all of the synthesized POSCI membranes had hydrophilic properties as their contact angle is less than 90 °.  Sol-gel analysis shows that the swelling ratio of POSCI decreases while the gel fraction increases with increasing in photocrosslinking time. The tensile strength of POSCI, thus, increased correspondingly with longer UV exposure. Excess DMPA, however, proved otherwise.