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Improved frame-by-frame object pose tracking in complex environments

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Abstract

Pose tracking is an important task in Augmented Reality (AR), interactive systems, and robotic systems. The frame-by-frame pose tracking that is effective in many cases still faces challenges in complex environments such as occlusions, illumination changes and flipping. In this paper, based on the optimization model offered by Ye et al. J Vis Commun Image Represent 44:72–81 (2017), three improvements are further proposed. First, a feature adjustment strategy based on a group of neighbors is offered to alleviate a sharp reduction of features. Then, when the features are no longer well representing the scene of interest, a score model based on a weighted histogram for result evaluations is presented to realize an adaptive interval. Besides, a forward-backward algorithm is provided to improve the accuracy by replacing the detection method with the tracking method. Experimental results manifest the effectiveness of the proposed algorithms.

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Notes

  1. https://www.dropbox.com/sh/4vgvzgmw5lsgziu/AAB_ucZ4AfBRuWp4et6g4ymHa?dl=0

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Acknowledgements

This work was supported by the National Natural Science Foundation of China [grant number 61373063, 61373062, 61473155]; the project of Ministry of Industry and Information Technology of China [grant number E0310/1112/02-1]; the Research Award Fund for Young Teachers of Education Department of Fujian Province [grant number JAT170037]; the Natural Science Foundation Project of Fujian Province [grant number 2017J01110]; the Science and Technology Planning Project of Fujian Province [grant number 2018H01010060]; the Science and Technology Planning Project of Quanzhou City, Fujian Province [grant number No.2017T003].

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Authors and Affiliations

  1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China

    Shuang Ye & Chuancai Liu

  2. School of Computer Science and Technology, Huaqiao University, Xiamen, 361021, China

    Shuang Ye

  3. Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau

    Zhiwu Li

  4. School of Electro-Mechanical Engineering, Xidian University, Xi’an, 710071, China

    Zhiwu Li

  5. Advanced Manufacturing Institute, King Saud University, Riyadh, 11421, Saudi Arabia

    Abdulrahman Al-Ahmari

  6. Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia

    Abdulrahman Al-Ahmari

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  1. Shuang Ye
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  2. Chuancai Liu
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  3. Zhiwu Li
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  4. Abdulrahman Al-Ahmari
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Correspondence to Chuancai Liu.

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Ye, S., Liu, C., Li, Z. et al. Improved frame-by-frame object pose tracking in complex environments. Multimed Tools Appl 77, 24983–25004 (2018). https://doi.org/10.1007/s11042-018-5736-8

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