2014/12/14 by Mansi Sharma, Santanu Chaudhury, Brejesh Lall · 1 citation
Computer Science · Engineering · #Advanced Vision and Imaging #Computer Graphics and Visualization Techniques #Advanced Optical Imaging Technologies
paper · doi:10.1145/2683483.2683555
openalex publication_date 2014/12/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
This paper addresses the challenges in creating good quality composite 3D contents for 3DTV applications and post-production visual-effects. We present a novel content-aware compositing technique that faithfully preserves the salient structures of cloned source and target content, and avoid major conflicting stereopsis cues to maintain a pleasant 3D illusion altogether. Our approach typically learns the appearance layouts of both source and target scene elements. The system extracts object's significance prior maps using classified labels and derive geometric transforms to compensate the 3D perspective mismatches between source and target images using a novel depth image-based rendering procedure. For seamless cloning, we apply a new depth-consistent interpolant technique which utilizes the classified likelihood confidences in weighting the salient or low-significant regions and re-estimating the plausible depth values of the cloned region in accordance with target 3D structure. Further, we adopt a novel content-preserving local warping scheme to reduce the apparent distortions in object shape, size and perspective. Finally, we propose a content-aware mean value cloning technique that seamlessly merges the warped cloned patches with the geometric-appearance context of new background and homogenize vague boundaries with the aid of an object salient map to remove the smudging effects. The overall process is formulated as an energy minimization problem and optimally regularized for large warps, vertical disparities, and stereo baseline changes. Plausible results are demonstrated to show the effectiveness of our approach.