A Filter-Driven Integral Image Generation Method for Scalable Image Resolution
Keywords:
integral image, computer vision, face recognition, object recognition, image resolutionAbstract
Integral images are widely used for computer vision applications such as face detection and object recognition because they can be utilized to speed up the feature computation step. In recent years, there has also been an increasing demand for the use of integral images in high-resolution computer vision applications. However, integral images need a significant amount of memory space since it exploits a large word length to represent the accumulation for filtering operations. There have been studies on the size reduction of the integral images such as word length reduction and partial accumulation methods. However, these approaches were not suited for high-resolution applications because their memory usage increases rapidly following the image resolution. Therefore, in this letter, we present a filter-driven integral image generation method for scalable integral image resolution. The proposed method generates integral images following the filter height which has much smaller dimension than the image resolution that the previous studies used. Consequently, the proposed filter-driven method is less affected by the image resolution of target applications. Evaluation results show the proposed method is scalable up to ultra-high definition (UHD) by reducing the memory usage by 76.4% compared with the state-of-the-art.
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(b)
Fig 2. Memory usage comparison of the integral image following
(a) the filter size and (b) the image resolution.
Note: filter height equals to filter width.
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