[DICOMO2019] 路側設置ステレオマイクを用いた車両種別推定手法の初期的評価 / Initial Evaluation of Vehicle Type Estimation using Sidewalk Stereo Microphones

Presented in DICOMO 2019, Fukushima, Japan

石田 繁巳, 内野 雅人, 小池 大地, 田頭 茂明, 福田 晃
路側設置ステレオマイクを用いた車両種別推定手法の初期的評価
情報処理学会マルチメディア, 分散, 協調とモバイルシンポジウム（DICOMO2019）, pp.1682-1687, Jul 2019
paper: http://id.nii.ac.jp/1001/00202424/
pdf: https://pman0214.netlify.app/static/9a26933151d0e007c5964f0628e614bd/ishida19-dicomo.pdf

Transcript

1.   
       *1,  *1, 
   *1,  *2,  *1 *1
   *2
   
2. 
    2
3. H> n ITS (Intelligent Transport System) • 1-;?% .@6$(&)B:, K)*I)+   n A • 6$<C4L 0" • MG#J • (3)!'59/ ⇒D7/8/=E  2F  3
4.  n    %* • #-+   ( • "$1)%* !./' 0%, &  ं྆૸ߦԻ
   ૸ߦํ޲
   ଎౓
   ं྆छผ
   ૸ߦंઢ
   
   
   4
5.   .; n '$ 8?7)SAVeD [Ishida+18] • O R0+19Q F83%
    n !*2 [Ishida+19] •  
   FG77% n ICB>6, 8?<A7) [Kubo+19] • #F 8?7)     ⇒MD7)8? J=5= [Ishida+18] ”SAVeD: Acoustic vehicle detector with speed estimation capable of sequential vehicle detection”, IEEE ITSC [Ishida+19] “Design of acoustic vehicle detector with stead—noise suppression”, IEEE ITSC (will appear) [Kubo+19] “KP
   "' @N-3&
   8?7)% /4 L:”, IPSJ ITSEH( 5
6. *-BE n JF%6>G:H) • KL3=YC9M/P [Aljaafreh+10] [Changjun+09] [Munich+04] • !#"D? [Yang+07] ⇒T36>JS 8U  n NJF%6>G:H) • ETC ⇒ &R4VO  • % !$;W7I [Hongliang+04] • 6>';W7I [Avery+04] ⇒X@Z[(Q,A+1<5<0.2 6 [Aljaafreh+10] “An evaluation of feature extraction methods for vehicle classification based on acoustic signals”, IEEE ISNSC [Changjun+09] “The research of vehicle classification using SVM and KNN in a ramp”, IFCSTA [Munich+04] “Bayesian subspace methods for acoustic signature recognition of vehicles”, EUSIPCO [Yang+07] “Vehicle identification using wireless sensor networks”, IEEE SoutheastCon [Hongliang+04] “A hybrid license plate extraction method baed on edge statistics and morphology”, ICPR [Avery+04] “Length-based vehicle classification using images from uncalibrated video cameras”, IEEE ITSC
7.   
     7
8. ! n %
    +  ", •  # %  '* ⇒ %  !
   + -)( & $ 8 Vehicle Sound t t t t Left Right Vehicle sound arrives at slight different time depending on vehicle location Compensate the time difference Emphasized Sound ∆t ∆t
9.  ( 9 1. $&  $& 2.    • '"!Δ" 3.   Δ"  
   $&  4. #%  # % ڧௐ߹੒ ಛ௃ྔ நग़ ं྆ݕग़ ं྆छผ ਪఆ Ϧϯά όοϑΝ ग़ྗ ӈ ࠨ ड৴࣌ؒࠩ t <latexit sha1_base64="Y8XyGa0wQXrnyWmNBE7p+7qu1ic=">AAAB8XicZVBNS8NAEJ3Urxq/qh69LJZCTyURQY8FPXisYD+gDWWz3bZLN5uwOxFK6J/wJnoQr/4dL/4bt20Q2z4YeLw3w8y8MJHCoOf9OIWt7Z3dveK+e3B4dHxSOj1rmTjVjDdZLGPdCanhUijeRIGSdxLNaRRK3g4nd3O//cy1EbF6wmnCg4iOlBgKRtFKnd49l0gJ9ktlr+YtQDaJn5My5Gj0S9+9QczSiCtkkhrT9b0Eg4xqFEzymVvppYYnlE3oiHctVTTiJsgWB89IxSoDMoy1LYVkobr/JjIaGTONQtsZURybdW8u/nmrq3B4G2RCJSlyxZabhqkkGJP5+2QgNGcop5ZQpoW9lrAx1ZShDcm1MfjrT2+S1lXNt/zxulyv5oEU4QIuoQo+3EAdHqABTWAg4QXe4N0xzqvz4XwuWwtOPnMOK3C+fgFwao/g</latexit> <latexit sha1_base64="Y8XyGa0wQXrnyWmNBE7p+7qu1ic=">AAAB8XicZVBNS8NAEJ3Urxq/qh69LJZCTyURQY8FPXisYD+gDWWz3bZLN5uwOxFK6J/wJnoQr/4dL/4bt20Q2z4YeLw3w8y8MJHCoOf9OIWt7Z3dveK+e3B4dHxSOj1rmTjVjDdZLGPdCanhUijeRIGSdxLNaRRK3g4nd3O//cy1EbF6wmnCg4iOlBgKRtFKnd49l0gJ9ktlr+YtQDaJn5My5Gj0S9+9QczSiCtkkhrT9b0Eg4xqFEzymVvppYYnlE3oiHctVTTiJsgWB89IxSoDMoy1LYVkobr/JjIaGTONQtsZURybdW8u/nmrq3B4G2RCJSlyxZabhqkkGJP5+2QgNGcop5ZQpoW9lrAx1ZShDcm1MfjrT2+S1lXNt/zxulyv5oEU4QIuoQo+3EAdHqABTWAg4QXe4N0xzqvz4XwuWwtOPnMOK3C+fgFwao/g</latexit> <latexit sha1_base64="Y8XyGa0wQXrnyWmNBE7p+7qu1ic=">AAAB8XicZVBNS8NAEJ3Urxq/qh69LJZCTyURQY8FPXisYD+gDWWz3bZLN5uwOxFK6J/wJnoQr/4dL/4bt20Q2z4YeLw3w8y8MJHCoOf9OIWt7Z3dveK+e3B4dHxSOj1rmTjVjDdZLGPdCanhUijeRIGSdxLNaRRK3g4nd3O//cy1EbF6wmnCg4iOlBgKRtFKnd49l0gJ9ktlr+YtQDaJn5My5Gj0S9+9QczSiCtkkhrT9b0Eg4xqFEzymVvppYYnlE3oiHctVTTiJsgWB89IxSoDMoy1LYVkobr/JjIaGTONQtsZURybdW8u/nmrq3B4G2RCJSlyxZabhqkkGJP5+2QgNGcop5ZQpoW9lrAx1ZShDcm1MfjrT2+S1lXNt/zxulyv5oEU4QIuoQo+3EAdHqABTWAg4QXe4N0xzqvz4XwuWwtOPnMOK3C+fgFwao/g</latexit> <latexit sha1_base64="Y8XyGa0wQXrnyWmNBE7p+7qu1ic=">AAAB8XicZVBNS8NAEJ3Urxq/qh69LJZCTyURQY8FPXisYD+gDWWz3bZLN5uwOxFK6J/wJnoQr/4dL/4bt20Q2z4YeLw3w8y8MJHCoOf9OIWt7Z3dveK+e3B4dHxSOj1rmTjVjDdZLGPdCanhUijeRIGSdxLNaRRK3g4nd3O//cy1EbF6wmnCg4iOlBgKRtFKnd49l0gJ9ktlr+YtQDaJn5My5Gj0S9+9QczSiCtkkhrT9b0Eg4xqFEzymVvppYYnlE3oiHctVTTiJsgWB89IxSoDMoy1LYVkobr/JjIaGTONQtsZURybdW8u/nmrq3B4G2RCJSlyxZabhqkkGJP5+2QgNGcop5ZQpoW9lrAx1ZShDcm1MfjrT2+S1lXNt/zxulyv5oEU4QIuoQo+3EAdHqABTWAg4QXe4N0xzqvz4XwuWwtOPnMOK3C+fgFwao/g</latexit> sR(t) <latexit sha1_base64="(null)">(null)</latexit> <latexit sha1_base64="(null)">(null)</latexit> <latexit sha1_base64="(null)">(null)</latexit> <latexit sha1_base64="(null)">(null)</latexit> sL(t) <latexit sha1_base64="(null)">(null)</latexit> <latexit sha1_base64="(null)">(null)</latexit> <latexit sha1_base64="(null)">(null)</latexit> <latexit sha1_base64="(null)">(null)</latexit> semph(t) = sR(t) + sL(t + t) <latexit sha1_base64="me+KelPCr5RXIlkxgiV57yNhojY=">AAACGHicZZBNS8NAEIY3ftb6VfXoZbEIEbEkKuhFKOjBg4cqVgVTwmY7tYu7SdidCCX0V3jzn3gTPYhX8eK/cdMW8eOFhYd3ZpidN0qlMOh5n87Y+MTk1HRppjw7N7+wWFlavjBJpjk0eSITfRUxA1LE0ESBEq5SDUxFEi6j28OifnkH2ogkPsdeCi3FbmLREZyhtcLKlgkDxbCrVQ4q7fZd3KAH1IRnBWxaOHFxMzgCiYziRlipejVvIPof/BFUyUiNsPIRtBOeKYiRS2bMte+l2MqZRsEl9MvrQWYgZfyW3cC1xZgpMK18cFefrlunTTuJti9GOnDLPyZypozpqch2FjeYv7XC/K79XoWd/VYu4jRDiPlwUyeTFBNapETbQgNH2bPAuBb2t5R3mWYcbZZlG4P/9+j/cLFd83dq26e71bo7CqREVskacYlP9kidHJMGaRJO7skjeSYvzoPz5Lw6b8PWMWc0s0J+yXn/AuIXnYQ=</latexit> ૸ߦԻऔಘ
10. :$;*/-4,# 10 n SAVeD+) [Ishida+18] • !  :$; =7%&6> " >2 • RANSAC) S8
    " • ".05%<! =7%&6 Δ!(!)1# [Ishida+18] ”SAVeD: Acoustic vehicle detector with speed estimation capable of sequential vehicle detection”, IEEE ITSC D/2 M1 M2 x O d2 d1 D/2 L 39 40 41 42 Time [s] −1 . 5 −1 . 0 −0 . 5 0 . 0 0 . 5 1 . 0 1 . 5 Sound Delay [ms] • '3%<!% • 9(&
11.  11 1. '"
       2. %'" !* +$#Δ" 
     (), 3. &'" t Left Right t f f Prepare for windowed data f Shift in time and add to right- channel data FFT FFT
12. n 67% SVM • 4 , #0  n ,:2 • 10kHz& 67%$; • 67%$ .! 1"'9LPF )-3*4 12  
     5+! ( 8 (SVM) )-/
13. 
     13
14. <*75 (1) n > =$  %6 • ?.1(4&2(4 • AZDEN SGM-990 SONY HDR-MV1 •  A! = 50cm • %6 @; # = 3m or 6m • 20@48kHz, 16bit n +9"1 #) n 100,8'-100! • 3(2:/  14 !"#$%&'%()* +,-.()/0%.1 0)#%$1)$
15. 9.64 (2) 15 n +,2$1 : ->70 8# n ,270(: 3 • =$,46/78/18/$1 n 5%);: 320ms n FFT : 4096' (≅85.3ms) • 25%  n ,2$1": "#$%% = 2.0s • ,2$1< ! *"#$%% & 9. ⇒3FFT  ,270 8#
16.   16 ⇒ 4.71% •  normal bike bus Estimated Type normal bike bus Actual Type 89.06 7.44 3.49 8.54 87.33 4.13 2.92 2.58 94.50 normal bike bus Estimated Type normal bike bus Actual Type 94.24 3.74 2.02 4.38 93.49 2.13 1.59 1.11 97.30
     : 90.30%
      (): 95.01%
17. -6 17 n )35198 &7 • :)5.18%6.16%2.79% ⇒,*")32 /4 • 2'  /4#0+  n )351 2.%  
       (.% 46 78 18 142 !$2.% 17 (36.96%) 43 (55.13%) 5 (27.78%) 65 (45.77%)
18. 
     18
19.  n ITS DK(.&.% • DK 6J  BI  n ')-"+!$ GDK(.&.% • Z=DLDKC08;A • Z=-.DKW 1TDK O Q  W E[ DKRI S4 n X/V?#,.*'5@MUF8N • Y795.01%DKRI S4  • 239<6JDK>:PH   19
20. © 2019 Shigemi ISHIDA licensed under CC BY-NC 4.0