一级黄色片免费播放|中国黄色视频播放片|日本三级a|可以直接考播黄片影视免费一级毛片

高級(jí)搜索

留言板

尊敬的讀者、作者、審稿人, 關(guān)于本刊的投稿、審稿、編輯和出版的任何問(wèn)題, 您可以本頁(yè)添加留言。我們將盡快給您答復(fù)。謝謝您的支持!

姓名
郵箱
手機(jī)號(hào)碼
標(biāo)題
留言內(nèi)容
驗(yàn)證碼

車載視頻下改進(jìn)的核相關(guān)濾波跟蹤算法

黃立勤 朱飄

黃立勤, 朱飄. 車載視頻下改進(jìn)的核相關(guān)濾波跟蹤算法[J]. 電子與信息學(xué)報(bào), 2018, 40(8): 1887-1894. doi: 10.11999/JEIT171109
引用本文: 黃立勤, 朱飄. 車載視頻下改進(jìn)的核相關(guān)濾波跟蹤算法[J]. 電子與信息學(xué)報(bào), 2018, 40(8): 1887-1894. doi: 10.11999/JEIT171109
HUANG Liqin, ZHU Piao. Improved Kernel Correlation Filtering Tracking for Vehicle Video[J]. Journal of Electronics & Information Technology, 2018, 40(8): 1887-1894. doi: 10.11999/JEIT171109
Citation: HUANG Liqin, ZHU Piao. Improved Kernel Correlation Filtering Tracking for Vehicle Video[J]. Journal of Electronics & Information Technology, 2018, 40(8): 1887-1894. doi: 10.11999/JEIT171109

車載視頻下改進(jìn)的核相關(guān)濾波跟蹤算法

doi: 10.11999/JEIT171109 cstr: 32379.14.JEIT171109
基金項(xiàng)目: 

國(guó)家自然科學(xué)基金(61471124),福建省重大重點(diǎn)科技項(xiàng)目(2017H6009, 2018H0018),賽爾網(wǎng)絡(luò)創(chuàng)新項(xiàng)目(NGII20160208, NGII20170201)

Improved Kernel Correlation Filtering Tracking for Vehicle Video

Funds: 

The National Natural Science Foundation of China (61471124), The Major Science and Technology Projects in Fujian Proviuce (2017H6009, 2018H0018), The Cernet Innovation Projects (NGII20160208, NGII20170201)

  • 摘要: 針對(duì)相關(guān)濾波跟蹤算法在車載視頻下由于環(huán)境復(fù)雜及目標(biāo)尺度變化等情況下容易跟蹤失敗的問(wèn)題,該文提出一種基于背景信息的尺度自適應(yīng)相關(guān)濾波跟蹤算法。首先利用背景感知相關(guān)濾波跟蹤器融合方向梯度直方圖特征預(yù)測(cè)目標(biāo)下一幀位置,然后根據(jù)預(yù)測(cè)位置選取圖像塊進(jìn)行檢測(cè),最后結(jié)合動(dòng)態(tài)尺度比例金字塔模型對(duì)目標(biāo)進(jìn)行尺度估計(jì)。實(shí)驗(yàn)選取了KITTI數(shù)據(jù)庫(kù)中23段車載視頻和標(biāo)注國(guó)內(nèi)的4段車載視頻進(jìn)行測(cè)試,實(shí)驗(yàn)結(jié)果表明,該算法能有效降低車載環(huán)境的復(fù)雜背景、目標(biāo)尺度變化等因素干擾,整體性能優(yōu)于KCF, DSST, SAMF, SATPLE等主流相關(guān)濾波算法,對(duì)車載環(huán)境下復(fù)雜背景和尺度變化的目標(biāo)跟蹤具有魯棒性。
  • 劉紅亮, 周生華, 劉宏偉, 等. 一種航跡恒虛警的目標(biāo)檢測(cè)跟蹤一體化算法[J]. 電子與信息學(xué)報(bào), 2016, 38(5): 1072-1078. doi: 10.11999/JEIT150638. LIU Hongliang, ZHOU Shenghua, LIU Hongwei, et al. An integrated target detection and tracking algorithm with constant track false alarm rate[J]. Journal of Electronics Information Technology, 2016, 38(5): 1072-1078. doi: 10.11999/JEIT150638.
    BOLME D S, BEVERIDGE J R, DRAPER B A, et al. Visual object tracking using adaptive correlation filters[C]. Computer Vision and Pattern Recognition, San Francisco, 2010: 2544-2550.
    HENRIQUES J F, RUI C, MARTINS P, et al. Exploiting the circulant structure of tracking-by-detection with kernels[C]. European Conference on Computer Vision, Florence, 2012: 702-715.
    HENRIQUES J F, RUI C, MARTINS P, et al. High-speed tracking with kernelized correlation filters[J]. IEEE Transactions on Pattern Analysis Machine Intelligence, 2015, 37(3): 583-596. doi: 10.1109/tpami.2014.2345390.
    畢篤彥, 庫(kù)濤, 查宇飛, 等. 基于顏色屬性直方圖的尺度目標(biāo)跟蹤算法研究[J]. 電子與信息學(xué)報(bào), 2016, 38(5): 1099-1106. doi: 10.11999/JEIT150921. BI Duyan, KU Tao, ZHA Yufei, et al. Scale-adaptive object tracking based on color names histogram[J]. Journal of Electronics Information Technology, 2016, 38(5): 1099-1106. doi: 10.11999/JEIT150921.
    QI Yuankai, ZHANG Shengping, QIN Lei, et al. Hedged deep tracking[J]. Computer Vision and Pattern Recognition, 2016, 4303-4311. doi: 10.1109/cvpr.2016.466.
    DANELLJAN M, HGER G, KHAN F S, et al. Accurate Scale Estimation for Robust Visual Tracking[C]. British Machine Vision Conference, Nottingham, 2014: 61-65.
    LI Yang and ZHU Jianke. A scale adaptive kernel correlation filter tracker with feature integration[C]. Eu-ropean Conference on Computer Vision, 2014, 8926: 254-265. doi: 10.1007/978-3-319-16181-5_18.
    XU Yulong, WANG Jiabao, LI Hang, et al. Patch-based scale calculation for real-time visual tracking[J]. IEEE Signal Processing Letters, 2015, 23(1): 40-44. doi: 10.1109/wcsp. 2015.7341015.
    AKIN O, ERDEM E, ERDEM A, et al. Deformable part- based tracking by coupled global and local corr-elation filters[J]. Journal of Visual Communication Image Representation, 2016, 38(C): 763-774. doi: 10.1016/j.jvcir. 2016.04.018.
    YAO Rui, XIA Shixiong, SHEN Fumin, et al. Exploiting spatial structure from parts for adaptive kerneli-zed correlation filter tracker[J]. IEEE Signal Processing Letters, 2016, 23(5): 658-662. doi: 10.1109/lsp.2016.2545705.
    CAMPLANI M, HANNUNA S, MIRMEHDI M, et al. Real- time RGB-D tracking with depth scaling kern-elised correlation filters and occlusion handling[C]. British Machine Vision Conference, SWANSEA, 2015. 2015: 141-145. doi: 10.5244/c.29.145.
    MA Chao, HUANG Jiabin, YANG Xiaokang, et al. Robust Visual Tracking via Hierarchical Convolutional Features[J]. Computer Vision and Pattern Recognition, 2017, (2017): 425-434. doi: 10.1007/978-3-319-70090-8_44.
    DANELLJAN M, BHAT G, KHAN F S, et al. ECO: Efficient convolution operators for tracking[C]. Computer Vision and Pattern Recognition, Honolulu, 2017: 21-26. doi: 10.1109/ cvpr.2017.733.
    DANELLJAN M, HAGER G, KHAN F S, et al. Learning spatially regularized correlation filters for visua-l tracking[C]. International Conference on Computer Vision, Santiago, 2015: 4310-4318. doi: 10.1109/iccv.2015.490.
    GALOOGAHI H K, FAGG A, and LUCEY S. Learning background-aware correlation filters for visual tracking[J]. 2017 IEEE International Conference on Computer Vision (ICCV), Venice, 2017: 21-26. doi: 10.1109/iccv.2017.129.
    DANELLJAN M, KHAN F S, FELSBERG M, et al. Adaptive color attributes for real-time visual tracking[C]. Computer Vision and Pattern Recognition,Washington, 2014: 1090-1097.
    GALOOGAHI H K, SIM T, and LUCEY S. Multi-channel correlation filters[C]. IEEE International Confer-ence on Computer Vision, Sydney, 2013: 3072-3079.
    RUI C and BATISTA J. Beyond hard negative mining: efficient detector learning via block-circulant deco- mposition[C]. IEEE International Conference on Computer Vision, Sydney, 2013: 2760-2767.
    BODDETI V N, KANADE T, and KUMAR B V K V. Correlation filters for object alignment[C]. Computer Vision and Pattern Recognition (CVPR), Portland, 2013: 2291-2298.
    MUELLER M, SMITH N, and GHANEM B. Context-aware correlation filter tracking[C]. IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, 2017: 1387-1395.
    GEIGER A, LENZ P, STILLER C, et al. Vision meets robotics: the KITTI dataset[J]. International Journal of Robotics Research, 2013, 32(11): 1231-1237. doi: 10.1177/ 0278364913491297.
    WU Yi, LIM Jongwoo, and YANG Minghsuan. Online object tracking: A benchmark[C]. Computer Vision and Pattern Recognition, Portland, 2013: 2411-2418.
    BERTINETTO L, VALMADRE J, GOLODETZ S, et al. Staple: Complementary learners for real-time trac-king[C]. Computer Vision and Pattern Recognition, Las Vegas, 2016: 1401-1409.
  • 加載中
計(jì)量
  • 文章訪問(wèn)數(shù):  1152
  • HTML全文瀏覽量:  162
  • PDF下載量:  105
  • 被引次數(shù): 0
出版歷程
  • 收稿日期:  2017-11-27
  • 修回日期:  2018-04-18
  • 刊出日期:  2018-08-19

目錄

    /

    返回文章
    返回