Overview
Kucherechedzwa kwechiito ibasa rekudzidzisa makomputa kuona zviri kuitwa nevanhu kana zvinhu * muvhidhiyo - kumhanya, kuzunguza, kudonha, kuvhura gonhi - kwete izvo zvinoonekwa mufuremu imwe chete. Izvo zvine basa nekuti kunzwisisa mafambiro nekufamba kwenguva kunovhura maapplication kubva kumitambo analytics kusvika kune vakura vanodonha kuonekwa.
Action Recognition ndeyekombuta-yekuona workflows inodudzira kana kuburitsa midhiya yekuona yekuongorora, mashandiro, uye kugadzira.
Deep Dive
Kuzivikanwa kwechiito kunodarika kusarudzika kwemifananidzo nekufunga nezvekuti mapixel anochinja sei nguva dzese. Furemu imwe chete inogona kuratidza munhu pakati pemhepo; kutevedzana chete kunoratidza kuti vari kusvetuka, kudonha, kana kunyura. Masisitimu ekutanga akagadzirwa nemaoko ekufambisa maficha senge optical kuyerera uye dense trajectories. Nzira dzemazuva ano dzinoshandisa mambure akadzika: maviri-rukova architectures process maitiro (RGB mafuremu) uye kufamba (optical flow) zvakasiyana; 3D convolutional network (seC3D neI3D) inotsvedza mafirita kuburikidza nenzvimbo *uye* nguva; uye vhidhiyo vashanduri (TimeSformer, VideoMAE) vanoisa kutarisisa pane ese spatio-temporal zvigamba. Mabhenji akajairwa anosanganisira Kinetics (700 makirasi echiito chevanhu kubva kuYouTube), UCF101, uye Chimwe Chinhu-Chimwe Chinhu, chinomanikidza mamodheru kuti anzwisise kutungamira kwechinguva kwete kungoita mamiriro echiitiko.
Technical Insight
Dambudziko guru nderekuenzanisa chiyero chenguva. Iyo 3D convolution inowedzera yakajairika 2D sefa ine yakadzika axis inotenderera akati wandei mafuremu, saka inodzidza mafambiro ekufamba zvakananga. Iyo I3D trick 'inokwidza' huremu kubva kune 2D mufananidzo network yakafanodzidziswa paImageNet kupinda mu3D nekuidzokorora nguva dzese, ichipa pekutangira yakasimba. Nzira mbiri-yerukova panzvimbo inodyisa precomputed optical kuyerera kupinda mubazi rakasiyana, zvakajeka encoding mafambiro uye wobva waisanganisa nezvitarisiko.
Mastering Action Recognition
Kucherechedzwa kwechiito ibasa rekudzidzisa makomputa kuona zviri kuitwa nevanhu kana zvinhu * muvhidhiyo - kumhanya, kuzunguza, kudonha, kuvhura gonhi - kwete izvo zvinoonekwa mufuremu imwe chete. Izvo zvine basa nekuti kunzwisisa mafambiro nekufamba kwenguva kunovhura maapplication kubva kumitambo analytics kusvika kune vakura vanodonha kuonekwa. Action Recognition ndeyekombuta-yekuona workflows inodudzira kana kuburitsa midhiya yekuona yekuongorora, mashandiro, uye kugadzira. Kuti uvake kunzwisisa kwakadzama, bata Action Recognition semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvinodiwa, tsanangura fungidziro, uye patsanura zvinogona kuitwa nehurongwa hwakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Action Recognition chiyero chechokwadi nemashandiro anoita semhando yedata, kusiyana kwemwenje, uye kuenderana kwemazita. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero. Panguva imwecheteyo, kodzero dzeMufananidzo uye kubvumirwa kunogona kuve njodzi dzepamutemo kana hunhu husina kujeka. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero.
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Zvikwata zvekugadzira zvinogona prototype pfungwa nekukurumidza nekudzokororwa kwemaoko mashoma.
Zvikwata zvekugadzira zvinogona prototype pfungwa nekukurumidza nekudzokororwa kwemaoko mashoma. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Mashandisirwo anogona kushandisa masaini emifananidzo nemavhidhiyo ayo aimbove akaoma kugadzirisa.
Mashandisirwo anogona kushandisa masaini emifananidzo nemavhidhiyo ayo aimbove akaoma kugadzirisa. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
Kudonha-yekuona masisitimu mudzimba dzevakweguru inozivisa vashandi kana mugari akadonha, kusiyanisa kudonha kubva pakugara kana kurara pasi.
Sports analytics mapuratifomu ayo anogadzika tag anoshanda, mabatiro, uye mapfuti mumitambo yemitambo yekudzidzisa uye kutepfenyura zvakakwirira.
Kutarisisa uye kuchengetedzwa kwekutarisa kunoratidza maitiro asina kujairika sekurwa, kudzungaira, kana mumwe munhu kukwira fenzi.
Gesture-inodzorwa maratidziro uye kusimba maapplication anoverenga reps uye kutarisa fomu rekurovedza muviri nekuziva mafambiro emuviri nekufamba kwenguva.
Maitiro Ekuita
Chiito Kuzivikanwa mukuita
Kudonha-kuona masisitimu mudzimba dzevakweguru dzinozivisa vashandi kana mugari adonha, kusiyanisa kudonha kubva pakugara kana kurara pasi.
Kudonha-kuona masisitimu mudzimba dzevakweguru dzinozivisa vashandi kana mugari adonha, kusiyanisa kudonha kubva pakugara kana kurara pasi Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura mhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yekesi dzemupendero, uye kuteedzera zvese zvakawanikwa mukubudirira uye kukanganisa mutengo nekufamba kwenguva.
Chiito Kuzivikanwa mukuita
Sports analytics mapuratifomu ayo anogadzika tag anoshanda, mabatiro, uye mapfuti mumitambo yemitambo yekudzidzisa uye kutepfenyura makwikwi.
Sports analytics mapuratifomu ayo anongoshanda, anorova, uye mapfuti mumachisi emitambo yekudzidzisa uye kutepfenyura maratidziro Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura hunhu hwepamberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Chiito Kuzivikanwa mukuita
Kutariswa nekuchengetedzwa kwekuchengetedza izvo zvinoratidzira maitiro asina kujairika sekurwa, kudzungaira, kana mumwe munhu kukwira fenzi.
Kuongorora uye kuchengetedzwa kwekutarisa mureza hunhu husina kujairika sekurwa, kudzungaira, kana mumwe munhu anokwira fenzi Matimu anowanzo kuwana mibairo iri nani kana achinge atsanangura zvikumbaridzo zvemhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa mukubudirira nemitengo yekukanganisa nekufamba kwenguva.
Chiito Kuzivikanwa mukuita
Gesture-inodzorwa maratidziro uye kusimba maapplication anoverenga reps uye tarisa maekisesaizi fomu nekuziva mafambiro emuviri nekufamba kwenguva.
Gesture-inodzorwa maratidziro uye kusimba maapplication ayo anoverenga reps uye tarisa fomu rekurovedza muviri nekuziva mafambiro emuviri nekufamba kwenguva Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Njodzi & Guardrails
Kodzero dzemifananidzo uye kubvumirwa kunogona kuve njodzi dzepamutemo kana provenance isina kujeka.
Kuita kwemuenzaniso kunogona kusiyanisa kupenya, huwandu hwevanhu, uye nharaunda.
Manyepo enhema anogona kusacherechedzwa kunze kwekunge zvikumbaridzo zvekuvimba zvikatariswa.
Implementation Roadmap
Tsanangura maitiro ekugamuchirwa echokwadi, kurangarira, uye mutengo wekukanganisa.
Tsanangura maitiro ekugamuchirwa echokwadi, kurangarira, uye mutengo wekukanganisa. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Edzai nedata rinoenderana nemamiriro chaiwo ekugadzira.
Edzai nedata rinoenderana nemamiriro chaiwo ekugadzira. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Wedzera ongororo yemunhu kune yakaderera-kusavimbika kana yakakwirira-inokanganisa kufanotaura.
Wedzera ongororo yemunhu kune yakaderera-kusavimbika kana yakakwirira-inokanganisa kufanotaura. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Tevera modhi kudonha uye simbisa mushure mekuchinja kwekamera kana dataset.
Tevera modhi kudonha uye simbisa mushure mekuchinja kwekamera kana dataset. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.