Physically Based Video Editing

Bazin, Jean-Charles; Plüss (Kuster), Claudia; Yu, Guo; Martin, Tobias; Jacobson, Alec; Gross, Markus

Convincing manipulation of objects in live action videos is a difficult and often tedious task. Skilled video editors achieve this with the help of modern professional tools, but complex motions might still lack physical realism since existing tools do not consider the laws of physics. On the other hand, physically based simulation promises a high degree of realism, but typically creates a virtual 3D scene animation rather than returning an edited version of an input live action video. We propose a framework that combines video editing and physics-based simulation. Our tool assists unskilled users in editing an input image or video while respecting the laws of physics and also leveraging the image content. We first fit a physically based simulation that approximates the object’s motion in the input video. We then allow the user to edit the physical parameters of the object, generating a new physical behavior for it. The core of our work is the formulation of an image-aware constraint within physics simulations. This constraint manifests as external control forces to guide the object in a way that encourages proper texturing at every frame, yet producing physically plausible motions. We demonstrate the generality of our method on a variety of physical interactions: rigid motion, multi-body collisions, clothes and elastic bodies.

Physically Based Video Editing

 

Efficient and Reliable Self-Collision Culling using Unprojected Normal Cones

Tongtong Wang, Zhihua Liu, Min Tang, Roufeng Tong, and Dinesh Manocha

We present an efficient and accurate algorithm for self-collision detection in deformable models. Our approach can perform discrete and continuous collision queries on triangulated meshes. We present a simple and linear time algorithm to perform the normal cone test using the unprojected 3D vertices, which reduces to a sequence point-plane classification tests. Moreover, we present a hierarchical traversal scheme that can significantly reduce the number of normal cone tests and the memory overhead using front-based normal cone culling. The overall algorithm can reliably detect all (self) collisions in models composed of hundred of thousands of triangles. We observe considerable performance improvement over prior CCD algorithms.

Efficient and Reliable Self-Collision Culling using Unprojected Normal Cones

Eurographics 2017

Interactive Paper Tearing

Camille Schreck, Damien Rohmer, Stefanie Hahmann

We propose an efficient method to model paper tearing in the context of interactive modeling. The method uses geometrical information to automatically detect potential starting points of tears. We further introduce a new hybrid geometrical and physical-based method to compute the trajectory of tears while procedurally synthesizing high resolution details of the tearing path using a texture based approach. The results obtained are compared with real paper and with previous studies on the expected geometric paths of paper that tears.

Interactive Paper Tearing