Limited by the performance factor, it is arduous to recognize target object and locate it in Augmented Reality (AR) scenes on low-end mobile devices, especially which using monocular cameras. In this paper, we proposed an algorithm which can quickly locate the target object through image object detection in the circumstances of having very sparse feature points. We introduce YOLOv3-Tiny to our algorithm as the object detection module to filter the possible points and using Principal Component Analysis (PCA) to determine the location. We conduct the experiment in a manually designed scene by holding a smartphone and the results represent high positioning speed and accuracy of our method.
翻译:由于性能因素的限制,很难辨别目标对象,并将其定位在低端移动设备上增强现实(AR)场景中,特别是使用单筒照相机的场景中。在本文中,我们提出了一个算法,在特征点非常稀少的情况下,可以通过图像物体探测迅速定位目标对象。我们将YOLOv3-Tiny引入我们的算法作为物体探测模块,以过滤可能的点,并使用主元件分析(PCA)来确定位置。我们用智能手机在手工设计的场景中进行实验,结果代表了我们方法的高定位速度和精确度。