Object Modeling with Color Arrangement for Region-Based Tracking

被引:0
|
作者
Kim, Dae-Hwan [1 ]
Jung, Seung-Won [2 ]
Suryanto
Lee, Seung-Jun [1 ]
Kim, Hyo-Kak [1 ]
Ko, Sung-Jea
机构
[1] Korea Univ, Dept Elect Engn, Multimedia Image Proc Lab, Seoul, South Korea
[2] Korea Univ, Res Inst Infommt & Commun Technol, Seoul, South Korea
关键词
Bhattacharyya coefficient; kernel-based tracking; mean shift; object tracking; spatiograms; ROBUST;
D O I
10.4218/etrij.11.0111.0383
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we propose a new color histogram model for object tracking. The proposed model incorporates the color arrangement of the target that encodes the relative spatial distribution of the colors inside the object. Using the color arrangement, we can determine which color bin is more reliable for tracking. Based on the proposed color histogram model, we derive a mean shift framework using a modified Bhattacharyya distance. In addition, we present a method of updating an object scale and a target model to cope with changes in the target appearance. Unlike conventional mean shift based methods, our algorithm produces satisfactory results even when the object being tracked shares similar colors with the background.
引用
收藏
页码:399 / 409
页数:11
相关论文
共 50 条
  • [1] Salient Region-Based Online Object Tracking
    Lee, Hyemin
    Kim, Daijin
    2018 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2018), 2018, : 1170 - 1177
  • [2] A region-based method for model-free object tracking
    Huang, Y
    Huang, TS
    Niemann, H
    16TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL I, PROCEEDINGS, 2002, : 592 - 595
  • [3] A region-based method for model-free object tracking
    Yu, Huang
    Huang, Thomas S.
    Niemann, Heinrich
    Proceedings - International Conference on Pattern Recognition, 2002, 16 (01): : 592 - 595
  • [4] A REGION-BASED PARTICLE FILTER FOR GENERIC OBJECT TRACKING AND SEGMENTATION
    Varas, David
    Marques, Ferran
    2012 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2012), 2012, : 1333 - 1336
  • [5] Video object segmentation and tracking using region-based statistics
    Erdem, Cigdem Eroglu
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2007, 22 (10) : 891 - 905
  • [6] Fast hybrid block/region-based algorithm for object tracking
    Jordan, F
    Schutz, M
    Kunt, M
    VIDEO TECHNIQUES AND SOFTWARE FOR FULL-SERVICE NETWORKS, 1997, 2915 : 96 - 107
  • [7] Semantic video object tracking using region-based classification
    Gu, C
    Lee, MC
    1998 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING - PROCEEDINGS, VOL 3, 1998, : 643 - 647
  • [8] Region-Based Object Recognition by Color Segmentation Using a Simplified PCNN
    Chen, Yuli
    Ma, Yide
    Kim, Dong Hwan
    Park, Sung-Kee
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 26 (08) : 1682 - 1697
  • [9] Region-based statistical background modeling for foreground object segmentation
    De Beek, Kristof Op
    Gu, Irene Yu-Hua
    Li, Liyuan
    Viberg, Mats
    De Moor, Bart
    2006 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2006, PROCEEDINGS, 2006, : 3317 - +
  • [10] Enhancing region-based object tracking with the SP-SIFT feature
    Navarro Fajardo, Fulgencio
    Escudero-Vinolo, Marcos
    Bescos Cano, Jesus
    2014 12TH INTERNATIONAL WORKSHOP ON CONTENT-BASED MULTIMEDIA INDEXING (CBMI), 2014,