Towards Better Methods of Stereoscopic 3D Media Adjustment and Stylization

Stereoscopic 3D (S3D) media is pervasive in film, photography and art. However, working with S3D media poses a number of interesting challenges arising from capture and editing. In this thesis we address several of these challenges. In particular, we address disparity adjustment and present a layer-based method that can reduce disparity without distorting the scene. Our method was successfully used to repair several images for the 2014 documentary “Soldiers’ Stories” directed by Jonathan Kitzen. We then explore consistent and comfortable methods for stylizing stereo images. Our approach uses a modified version of the layer-based technique used for disparity adjustment and can be used with a variety of stylization filters, including those in Adobe Photoshop. We also present a disparity-aware painterly rendering algorithm. A user study concluded that our layer-based stylization method produced S3D images that were more comfortable than previous methods. Finally, we address S3D line drawing from S3D photographs. Line drawing is a common art style that our layer-based method is not able to reproduce. To improve the depth perception of our line drawings we optionally add stylized shading. An expert survey concluded that our results were comfortable and reproduced a sense of depth

A Simple, Stroke-Based Method for Gesture Drawing

Background: Gesture drawing is a type of fluid, fast sketch with loose and roughly drawn lines which capture the motion and feeling of a subject. While style transfer methods, which are able to learn a style from an input image and apply it to a secondary image, can reproduce many styles, they are currently unable to produce the flowing strokes of gesture drawings. Method: In this paper, we present a method to produce gesture drawings, which roughly depict objects or scenes with loose, dancing contours, and frantic textures. Our method adapts stroke-based painterly rendering algorithms to produce long, curved strokes by following the gradient field. A rough, overdrawn appearance is created through progressive refinement. Additionally, we produce rough hatch strokes by altering stroke direction. These add optional shading to the gesture drawings. Results: The wealth parameters that provide users the ability to adjust the output style from short, rapid strokes to long, fluid strokes, from swirling to straight lines. Potential stylistic outputs also include pen-and-ink and coloured pencil. We present several generated gesture drawings and discuss how our method can be applied to video. Conclusion: Our stroke-based rendering algorithm produces convincing gesture drawings with numerous controllable parameters permitting the creation of a variety of styles