Techniques for vanishing point detection

Automatic vanishing point detection is an important problem in computer vision since it has many applications such as road navigation, 3D scene reconstruction and camera calibration. Accurate detection of the vanishing point location facilitates the solution of these related problems. For a given image, this research attempts to answer the following two questions: 1) whether there is vanishing point or not in this image; and 2) if there are vanishing points, where their locations are. To address the first question, we apply a machine learning approach. First, we construct a database containing a wide variety of images and use it to train a model to determine whether there is vanishing point in a test image. The two features used in this training and test process are the angular histogram and the defocus degree. Furthermore, we adopt the Adaboost algorithm as incremental learning to increase classification accuracy. To address the second problem, we implement and improve one algorithm for vanishing point location estimation, and compare its performance with another algorithm based on the J-linkage model. Finally, concluding remarks and future research directions are discussed.