We propose a GPU-based online patch learning algorithm for detection of a planar target object. The proposed algorithm learns the appearance of a planar region by computing warped patches seen from a set of viewpoints. To accelerate learning process, we replace patch warping with patch rendering on a mobile phone's GPU for fast warping and apply radial and Gaussian blurs to the rendered patch to reflect appearance differences caused by small pose disturbances.

Our learning algorithm automatically generates a frontal view of a patch based on an initial camera pose obtained by a built-in accelerometer of a mobile phone and thus, it does not require the frontal view of a patch, which is a common requirement of existing patch learning algorithms. In addition, our algorithm requires no prior knowledge and only the image of a planar region is required for learning. According to experiments, learning a patch takes only a few seconds on mobile phones. We expect our algorithm will be useful for mobile Augmented Reality (AR) tagging applications in the real world.