The　six　degree　of　freedom　based（6DoF-based）video　technique　is　featured　by　interaction　between　video　content　and　users，and　it　is　focused　on　its　1）linear-derived　multiple　capacities，2）horizontal　straightness，3）vertical　straightness，4）pitch，5）yaw，and　6）roll　motions　of　users.　In　this　manner，users　can　change　multiple　audio-visual　dimensions，including：viewing　perspective，lighting　condition　or　directions，focal　length　or　spot，field　of　view　through　ground　truth-compared　computational　or　synthesized　content　reconstruction.　The　6DoF　video　can　be　used　to　change　conventional　behavior　of　video　watching，in　which　the　user-video　interaction　is　limited　to　different　span　of　channels　and　the　relations　between　video　contents　is　restricted　as　well.　The　6DoF-based　technique　can　offer　immersive　experience　for　users　because　the　homogeneity　of　video-watching　receptive　content　can　be　in　consistency　per　their　motion.　In　this　way，the　6DoF　video　can　be　recognized　as　an　epoch-making　type　of　video　for　academia　and　industries.　At　the　same　time，metaverse-driven　6DoF　video　has　also　been　recognized　as　a　new　generation　of　interactive　media　technology，which　is　recognized　as　one　of　the　key　technologies　for　Metaversein　related　domains.　All　these　features　make　users　experience　feel　depth-immersive　and　diversified.　This　mutual-benefited　status　is　in　relevance　to　the　metaverse-based　perception，computing，reconstruction，collaboration，interaction，and　other　related　technical　features.　Basically，6DoF　video　is　originated　from　the　framework　of　typical　multimedia　communication　system，where　it　can　be　suitable　to　meet　the　basic　procedure　requirement　of　video-contextual　multimedia　communication　like　its　capturing，content　process，video　compression，transmission，decode　and　display.　To　realize　intelligent　human-terminal　interaction，it　brings　a　new　look　beyond　traditional　3D　video　communication　system，and　the　requirements　for　interaction　range　and　intelligence　are　still　acomplicated.　Therefore，such　newly　techniques　are　in　support　of　new　type　of　video　to　a　certain　extent.　Our　proposed　technical　framework　of　6DoF-relevant　multimedia　communication　system　is　demonstrated　on　the　three　aspects　of　generation，distribution，and　visualization.　Forty　scientific　and　technical　challenges　of　this　domain　are　illustrated　and　it　can　be　categorized　them　into　10　different　directions.　We　carry　out　literature　review　of　its　growth　of　per　one　of　these　10　directions　on　the　aspects　of　content　acquisition　and　pre-processing，coding　compression　and　transmission　optimization，interaction，and　presentation.　For　techniques　analysis，it　is　focused　on　such　aspects　of　1）con-tent　generation-derived　multiview　video-captured　content，2）multiview　video　plus　depth，and　3）point　cloud.　The　data-acquired　systems　can　be　categorized　by　2　types　of　multiview　and　multiview　plus　depth　system，and　different　types　of　contents　can　be　thus　obtained　via　these　systems.　To　describe　the　3D　structure　of　the　spot　scene　initially，multiview　color　videos　can　be　captured　without　any　affiliated　information，but　it　is　a　challenging　issue　for　subsequent　data　processing　techniques.　After　that，multiview　plus　depth　system　is　proposed　to　handle　this　problem，while　data　can　be　classified　into　two　types　of　i）color　plus　depth　and　ii）point　cloud.　Data-heteogenous　volume　is　a　big　challenge　for　these　kinds　of　data　representation　to　some　extent.　The　video　compression　techniques-after　can　be　focused　on　in　terms　of　the　video　contents.　Popular　compression　techniques　for　multiview　video，multiview　video　plus　depth，light　fields，and　point　clouds　are　discussed　further，including　their　origination，mechanism，performance，and　credible　application　standards.　Subsequently，transmission　techniques　for　6DoF　video　are　illustrated　as　well　after　the　video　bitstream　is　obtained.　Such　techniques　like　bit　allocation，interaction　oriented　transmission，standards　and　protocols　are　all　mentioned　and　discussed.　Its　quality　evaluation　and　synthesized-view　for　user-terminal　interaction　are　analyzed　as　well.　It　can　be　reached　to　user-friendly　in　terms　of　a“capture　to　display”based　6DoF　video　system.　Pixel-based　methods　are　still　discussed　and　optimized　but　computational　cost　is　challenged　there.　Recent　learning　based　methods　are　more　concerned　about　terminal-oriented　applications，especially　for　its　synthesized　view.　To　meet　the　requirements　from　practical　applications，40　scientific　and　technical　challenges　mentioned　above　are　still　to　be　resolved　further.　©　2023　Editorial　and　Publishing　Board　of　JIG.　All　rights　reserved.