For anyone who is interested, pretty cool stuff, UIT ( Vietnamese University of Information Technology) demonstrates a neural approach (YOLO5 + tracking + rotation) to improve the license plate recognition accuracy
Paper - 2307.11336.pdf
For anyone who is interested, pretty cool stuff, UIT ( Vietnamese University of Information Technology) demonstrates a neural approach (YOLO5 + tracking + rotation) to improve the license plate recognition accuracy
Paper - 2307.11336.pdf
*** ***** ****** **** *** *** datasets; ****-**** *** * ******* ******* gathered **** ****** ** ******* ** Vietnam.
********* *** ****** **********, ** ******** our ****** ** *** ****-**** ****** dataset *** *** ******* *******, ***** is ******** **** ******** ** ******* on *** ******* ** *******.
*** ****-**** *************** *,*** ****** ** *** ********* moving ********, ***** ** * ****** camera (*****/***** ******* ** * ***). Here ** ** ******* ***** **** the *******:
** *** *** ******* ******* ********* in *** *****, ***** ** ** available ****, ****** *** *** ******* provided ** *** *****. *** ******* say **** "**** ** * *** of *** ****** ******** **** ** cameras ** ****-***** **********." *** ******* in *** ***** ***** ******* ****** from * ******** ***** ** ********.
******* ******* *** **** **** *** data, ** ** *** ******** ** verify *** ******** ** *** ***********.
** *** **** ******** ****, *** paper ****** *** *********** ************ ** the ****-****** ********, ***** **** ** performed ****** ******** ******, *** *** license ***** *********** ** ********** *** the **** *****.
***** **** ***** ******* ******** ** theory, ** **** ********* ******* **** shots ** ******* ****** **** ******* angles ** ****** *** *** ***** with ****-****** **** **** *********** *** this ********.
** ******** *** ******** **** ****, ** ****** **** **** ********* such ** ***** **********, *** **********, who ************ ***** ********* ** ******* angles *** **** ****-****** ****.
*** ****-**** *************** *,*** ****** ** *** ********* moving ********, ***** ** * ****** camera (*****/***** ******* ** * ***).
**** ******* ** ** ************* *** materially ********* **** ***** *** ***** the ******* *** ** **** ***** horizontal *** ******** ******.
****** ****
* ***** **** ***** *** ***** main "******" **** ******* ** *** article -
*. ***** **** ** ****** (******* consecutive ****** ***** ** ***** *** object), *** *** ** ****** ***** recognition.
*. ******** - ** ********** *** cars ****** *** ******* ***** ***** changing *********** ******* ****** ** *** same *****, **** *** ** **** to **** ****** *** ***** ** all *** ****** ** *** ***** so ** **** ************ ** "*** angeled *****" (**** ****** **** ** each "**** *****" *** ***** *** in ********* ********* *** ***** ******* the **** *** ******)
*. ********* **** ****** ******** - After **** *, ** *** **** a "*****" (*.* ** ********) ***** all *** ****** *** "***** ******* in *** **** *********". ** **** point, **** ***** ********* ** ********* (since **** *** *** ********** ** same ******** *** **** *********), *** then ********* * ***** **** ******* frames. *.* ******* ** ***** * the ****** "*" ** **** *******, but ** ***** *-* **'* ** and ** *** ********* **'* "*" in **** ********** ** ** ***** it ****** *** *** ******
** ******* ** *** *****, ** you ** **** *** ********* "*** each ***** ** * **** ******* my *** ****" ********, *** **** to **** "*** *** ***** ** a ***" ******* *** *** ***** enough ** *** *** **** ***** in *** *** ***** ***** *** characters *** ********** ******* ** * point **** **** ******* ****.
**** *** ********* ****** ** *** paper, ** **** ****** *** ********** are ****** *** ** **** ****** it **** ** ***** ********** **** got ******, *** ** *** ******* them *** ****** ******* ******, *** can *** * **** ******
*** * ***** *** ******* ***** here ** **** **'* **** ****** with **** ******, *** ** *** POC'ed ** **** & ********* ******* roads. **** ** *********** ** ***** how ** ******** ** ********** "****" alternatives
***** ****: ******** *** **** ** not * ***/***** **********. **** ** a **** ***** ****** "* ************ ****** *** *****-***** ******* plate ***********", ***** ******** ** ********* *** ALPR. **** ** *** ****** **** that ***** ************ *** ******** *****.
********* **** ****** ********
*** *** ****** *******, ******** ** its *** ** *** ***/*****. **'* a ****** ******** ** ******** ****** as * *****
*** ***** ***** **** ******** ** not "***'* ** ******** ** **** frame ** * **** ******** *** chances ** ** *** **** ********* all **********" , *** "***'* *** rotation ** **** *** *** ********** are ***** ** *** **** ***** and * *** ***** **** *** by *** ****** ****** ** *** them ***"
* ****'* **** **** ** **** the ***** ** *****, *** ** seems **** **** *** ************* ** object ******* ** ******* *** ********* multiple ****** ** * ***** **** time. **** **** **** ** ***** frames **** *** *** ******* *** use * ********* ******** ***** ***** for *** ***** ** ** **** to "**** ** *** ******" ****** multiple ****** **** * **** ****** of ********.
** ***'** **** *********** *** ******* you've ******** **** *** ***** ***** you *** *** **** ***** ***'* multiple ***** **** ******** ********* ******, as ***** ******* *** **** ****** not ***** *** **** ** * tracker *** **** ******* *** ****** plates ****** **** **** ****. *** in **** ******** *** **** ***** can ** **** **** ********* *******, giving *** *** ********/********* *******.
*** ******** ****, **** **** * can **** ** *** *****, ** that **** ***'* ***** *** ******** and ******** ******* ***** ***** *** plate ** "****" ** *** *******, so *** *** ******* *******. **** likely **** *** ******* ****** *** later ******, **** ** ** *** public ************ *******, *** ***** ** less ***** *** ********* ***** *** want ** *** * ***** ** a **********, ** * ****-***** **** of ********.
*** *** ******* **** *** **** sample **** ******** **** ****** ********** after *** ***** ** ******** (** fact ** **** ***** **** ***** files *** *** ********* ** ***), but **** ** **** * ******** decision.
*** *** *** * **** ** code **** **** *** "***** ** done ** **'* ******* * ****** of ****** ** ** ****, ******** comes ******". *** **** *** *** in ****** **** ** * ****** for *** ******** ********* ** *** usecase (*.* *** * ***** ******, you *** *** "** *** ***** track ****** ** **, *** ***** get *** ******* * ******* *******. but *** ****** *** ****** **** number, ** ****** *** ******* ***** be ****** ******* *** ***** *** more ****** ** *** ***** ** improve *** ***** ********. ** *** put ** *****, *** **** *** the ******* ****** *** *** *** the ***** ****** **'* ******** ** you ***** **** **** **** ****** in **")
*** *** *** * **** ** code **** **** *** "***** ** done ** **'* ******* * ****** of ****** ** ** ****, ******** comes ******"
***** *** **** ***** ****** **** could **** ** **** ** ***** up ******, **** ******** *** **** of ***** *** ******** ******** ** decide **** ** ******* **. * large-ish ***** ****** **** **** (** stopped) ** **** ****** ***** ** give *** * **** ******** ****** than * ***** ***** ****** ****, where *** ***** **** **** *******.
** ******, ** **** ***** ** that ***'** ******* ******* ****** *** increased ********, ***** *** *** **** part *** **** * ******* ******* in ***** ********* ***** *******.
Ask questions and get answers to your physical security questions from IPVM team members and fellow subscribers.
*** ****** *** *******! ***********!
**** *** *****:
**'** ***** ******* ****** *** ******* and *********, ******** ** ********** **** though *** **** ****** ******** ***** with ****** ****** ******* *******.
*******:**** "***-**-***" *** *** ******,******* *** ******,******* ****** *********** *** ******,******** *** *****-****** *** ******
**** ******** *** *****, ****'* *** how **** **** ********* *** ******* of **** ***** ******* **** ******* one ** **** *** **** ***** when **** *** ****** **** ** as ** ***** ****** *** ***** of ******** **** *** ****** ** car ** ********* ****.
* ***** **** ** *******.