Biomedical subjects

Dinesh Manocha

Publications and source records attributed to Dinesh Manocha.

3 recordsLinked to original sources

PubMedDate not supplied

Incremental penetration depth estimation between convex polytopes using dual-space expansion.

We present a fast algorithm to estimate the penetration depth between convex polytopes in 3D. The algorithm incrementally seeks a "locally optimal solution" by walking on the surface of the Minkowski sums. The surface of the Minkowski sums is computed implicitly by constructing a local dual mapping on the Gauss map. We also present three heuristic techniques that are used to estimate the initial features used by the walking algorithm. We have implemented the algorithm and compared its performance with earlier approaches. In our experiments, the algorithm is able to estimate the penetration depth in about a milli-second on an 1 GHz Pentium PC. Moreover, its performance is almost independent of model complexity in environments with high coherence between successive instances.

Algorithms↗

PubMedDate not supplied

Quick-VDR: out-of-core view-dependent rendering of gigantic models.

We present a novel approach for interactive view-dependent rendering of massive models. Our algorithm combines view-dependent simplification, occlusion culling, and out-of-core rendering. We represent the model as a clustered hierarchy of progressive meshes (CHPM). We use the cluster hierarchy for coarse-grained selective refinement and progressive meshes for fine-grained local refinement. We present an out-of-core algorithm for computation of a CHPM that includes cluster decomposition, hierarchy generation, and simplification. We introduce novel cluster dependencies in the preprocess to generate crack-free, drastic simplifications at runtime. The clusters are used for LOD selection, occlusion culling, and out-of-core rendering. We add a frame of latency to the rendering pipeline to fetch newly visible clusters from the disk and avoid stalls. The CHPM reduces the refinement cost of view-dependent rendering by more than an order of magnitude as compared to a vertex hierarchy. We have implemented our algorithm on a desktop PC. We can render massive CAD, isosurface, and scanned models, consisting of tens or a few hundred million triangles at 15-35 frames per second with little loss in image quality.

Algorithms↗

PubMedDate not supplied

Fast and reliable collision culling using graphics hardware.

We present a reliable culling algorithm that enables fast and accurate collision detection between triangulated models in a complex environment. Our algorithm performs fast visibility queries on the GPUs for eliminating a subset of primitives that are not in close proximity. In order to overcome the accuracy problems caused by the limited viewport resolution, we compute the Minkowski sum of each primitive with a sphere and perform reliable 2.5D overlap tests between the primitives. We are able to achieve more effective collision culling as compared to prior object-space culling algorithms. We integrate our culling algorithm with CULLIDE [1] and use it to perform reliable GPU-based collision queries at interactive rates on all types of models, including nonmanifold geometry, deformable models, and breaking objects.

Algorithms↗