A Visual Marker based Image Annotation Tool with Projective Transformation

Although template matching has been studied for decades, difficult problems still exist, such as template matching with projective transformation. Projective template matching is challenging not only because of its own hardness, but also owing to the high cost in creating ground truths. Focusing on the problem in creating ground truths, in this paper, we propose a novel method to automatically create ground truth by augmented reality (AR) technology. Specifically, when creating dataset, around each target image we attach AR markers. Then we shoot videos containing target image with the markers from different angles and backgrounds. Finally we locate the target images by detecting the markers. We evaluate our method by deviation, intersection over union (IoU), and necessary correction rate, indicating that our method is available.