Laser & Optoelectronics Progress, Volume. 56, Issue 24, 241504(2019)
Hybrid Tracking Registration of Augmented Reality Based on Salience Detection
This study proposes a hybrid tracking registration method based on saliency detection for solving the insufficient robustness of tracking registration in a complex environment and the huge feature-searching space of the augmented reality system. Based on this method, the mean-shift iteration is initially employed to predict the candidate target position. Subsequently, a two-dimensional Gaussian function is constructed with a peak at the target center, and a visual saliency map of the fusion center prior is generated. Next, the target salient feature is extracted, and the mean-shift algorithm is applied to tracking. Furthermore, the similarity measurement coefficient is used to determine whether to utilize the deformation diversity similarity-matching algorithm for relocating the target. Finally, we construct a multiscale-space fast directional binary description algorithm that performs the feature detection and matching calculation with respect to the local target area to obtain the registration parameters, and the virtual-real fusion is completed. The experimental results demonstrate that the proposed method effectively solves the problems of tracking instability and low accuracy of target detection by using the target-tracking algorithm in the cases of background clutter, target occlusion, and target loss, improving the stability and robustness of the augmented reality system.
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Fanyi Gao, Jianwu Dang, Yangping Wang. Hybrid Tracking Registration of Augmented Reality Based on Salience Detection[J]. Laser & Optoelectronics Progress, 2019, 56(24): 241504
Category: Machine Vision
Received: Apr. 29, 2019
Accepted: Jun. 13, 2019
Published Online: Nov. 26, 2019
The Author Email: Dang Jianwu (dangjw@mail.lzjtu.cn), Wang Yangping (13519311970@163.com)