Aesthetics-Driven Stereoscopic 3-D Image Recomposition With Depth Adaptation

Abstract

Due to the availability and affordability of the stereoscopic equipment (e.g., stereo camera, lens, and display devices), stereoscopic image manipulation has been receiving considerable research attention in recent years. In this paper, we present a semiautomatic, aesthetic-driven stereoscopic image recomposition approach, which capacitates the change of the spatial position of the foreground object(s) in a given stereoscopic image to enhance human visual aesthetics. Our algorithm recomposes both the left and right stereo images simultaneously using a global optimization algorithm. To maximize image aesthetics, our algorithm minimizes a set of aesthetic quality errors, which is derived from selected photographic composition rules. In addition, depth adaptation is applied to the resized objects and change in vertical disparity of the resulting stereo image pair is minimized to ensure a pleasant three-dimensional (3-D) viewing experience. Our method can be used to perform stereoscopic image retargeting and recomposition simultaneously by providing the target image scale as the input. Empirical evaluations demonstrate the effectiveness of our approach in enhancing the aesthetics of stereoscopic 3-D images. Notably, depth adaptation is shown to play an important role in aesthetics enhancement.