Shading-Based Surface Editing

Yotam Gingold (NYU) and Denis Zorin (NYU)

We present a system for free-form surface modeling that allows a user to modify a shape by changing its rendered, shaded image using stroke-based drawing tools. User input is translated into a set of tangent and positional constraints on the surface. A new shape, whose rendered image closely approximates user input, is computed using an efficient and stable surface optimization procedure. We demonstrate how several types of free-form surface edits which may be difficult to cast in terms of standard deformation approaches can be easily performed using our system.


Optimized Scale-and-Stretch for Image Resizing

Yu-Shuen Wang (Cheng Kung University), Chiew-Lan Tai (HKUST), Olga Sorkine (NYU), Tong-Yee Lee (Cheng Kung University)

We present a “scale-and-stretch” warping method that allows resizing images into arbitrary aspect ratios while preserving visually prominent features. The method operates by iteratively computing optimal local scaling factors for each local region and updating a warped image that matches these scaling factors as closely as possible. The amount of deformation of the image content is guided by a significance map that characterizes the visual attractiveness of each pixel; this significance map is computed automatically using a combination of gradient and salience-based measures. Our technique allows diverting the distortion due to resizing to image regions with homogeneous content, such that the impact on perceptually important features is minimized.