siggraph08
A Meshless Hierarchical Representation for Light Transport
We introduce a meshless hierarchical representation for solving light transport problems. Precomputed radiance transfer (PRT) and finite elements require a discrete representation of illumination over the scene. Non-hierarchical approaches such as per-vertex values are simple to implement, but lead to long precomputation. Hierarchical bases like wavelets lead to dramatic acceleration, but in their basic form they work well only on flat or smooth surfaces. We introduce a hierarchical function basis induced by scattered data approximation. It is decoupled from the geometric representation, allowing the hierarchical representation of illumination on complex objects. We present simple data structures and algorithms for constructing and evaluating the basis functions.
We introduce a meshless hierarchical representation for solving light transport problems. Precomputed radiance transfer (PRT) and finite elements require a discrete representation of illumination over the scene. Non-hierarchical approaches such as per-vertex values are simple to implement, but lead to long precomputation. Hierarchical bases like wavelets lead to dramatic acceleration, but in their basic form they work well only on flat or smooth surfaces. We introduce a hierarchical function basis induced by scattered data approximation. It is decoupled from the geometric representation, allowing the hierarchical representation of illumination on complex objects. We present simple data structures and algorithms for constructing and evaluating the basis functions.
Articulated Mesh Animation from Multi-view Silhouettes
Details in mesh animations are difficult to generate but they have
great impact on visual quality. In this work, we demonstrate a practical
software system for capturing such details from multi-view
video recordings. Given a stream of synchronized video images
that record a human performance from multiple viewpoints and an
articulated template of the performer, our system captures the motion
of both the skeleton and the shape. The output mesh animation
is enhanced with the details observed in the image silhouettes. For
example, a performance in casual loose-fitting clothes will generate
mesh animations with flowing garment motions. We accomplish
this with a fast pose tracking method followed by nonrigid deformation
of the template to fit the silhouettes.
Details in mesh animations are difficult to generate but they have
great impact on visual quality. In this work, we demonstrate a practical
software system for capturing such details from multi-view
video recordings. Given a stream of synchronized video images
that record a human performance from multiple viewpoints and an
articulated template of the performer, our system captures the motion
of both the skeleton and the shape. The output mesh animation
is enhanced with the details observed in the image silhouettes. For
example, a performance in casual loose-fitting clothes will generate
mesh animations with flowing garment motions. We accomplish
this with a fast pose tracking method followed by nonrigid deformation
of the template to fit the silhouettes.
Hair Photobooth: Geometric and Photometric Acquisition of Real Hairstyles
We accurately capture the shape and appearance of a person's hairstyle. We use triangulation and a sweep with planes of light for the geometry. Multiple projectors and cameras address the challenges raised by the reflectance and intricate geometry of hair. We introduce the use of structure tensors to infer the hidden geometry between the hair surface and the scalp. Our triangulation approach affords substantial accuracy improvement and we are able to measure elaborate hair geometry including complex curls and concavities. To reproduce the hair appearance, we capture a six-dimensional reflectance field. We introduce a new reflectance interpolation technique that leverages an analytical reflectance model to alleviate cross-fading artifacts caused by linear methods.
We accurately capture the shape and appearance of a person's hairstyle. We use triangulation and a sweep with planes of light for the geometry. Multiple projectors and cameras address the challenges raised by the reflectance and intricate geometry of hair. We introduce the use of structure tensors to infer the hidden geometry between the hair surface and the scalp. Our triangulation approach affords substantial accuracy improvement and we are able to measure elaborate hair geometry including complex curls and concavities. To reproduce the hair appearance, we capture a six-dimensional reflectance field. We introduce a new reflectance interpolation technique that leverages an analytical reflectance model to alleviate cross-fading artifacts caused by linear methods.
