Wingo Sai-Keung Wong

RECODE: an image‐based collision detection algorithm

Object interactions are ubiquitous in interactive computer graphics, 3D object motion simulations, virtual reality and robotics applications. Most collision detection algorithms are based on geometrical object-space interference tests. Some algorithms have employed an image-space approach to the collision detection problem. In this paper we demonstrate an image-space collision detection process that allows substantial computational savings during the image-space interference test. This approach makes efficient use of the graphics rendering hardware for real-time complex object interactions. Copyright

Image-based techniques in a hybrid collision detector

Most collision detection methods developed so far are based on geometrical object-space interference tests. While this remains the basic mode of investigation for geometric algorithms, the requirements for interactive rates and complex geometry predominate in commercial applications. In this article, we propose a new mode of collision detection based on an image-space approach. This approach breaks the object-space collision detection bottleneck by distributing the computational load onto the hardware graphics pipeline. The image-space approach, in conjunction with efficient bounding-box strategies in the object-space, has the potential to handle complex object interactions at interactive rates.

Hardware-assisted self-collision for deformable surfaces

The natural behavior of garments and textile materials in the presence of changing object states is potentially the most computationally demanding task in a dynamic 3D virtual environment. Cloth materials are highly deformable inducing a very large number of contact points or regions with other objects. In a natural environment, cloth objects often interact with themselves generating a large number of self-collisions areas. The interactive requirements of 3D games and physically driven virtual environments make the cloth collisions and self-collisions computations more challenging. By exploiting mathematically well-defined smoothness conditions over smaller patches of deformable surfaces and resorting to image-based collision detection tests, we developed an efficient collision detection method that achieves interactive rates while tracking self-interactions in highly deformable surfaces consisting of more that 50,000 elements. The method makes use of a novel technique for dynamically generating a hierarchy of cloth bounding boxes in order to perform object-level culling and image-based intersection tests using conventional graphics hardware support.

A randomized marking scheme for continuous collision detection in simulation of deformable surfaces

Continuous collision detection techniques are applied extensively in the simulation of deformable surfaces, in particular for cloth simulation. Accurate contact information can be computed by using these techniques. Traditionally, for meshed surfaces, after collecting the triangle pairs that are potentially interacting, the feature pairs of these triangles are directly sent for the computation of collision information. Many feature pairs end up being processed repeatedly because a feature may be shared by more than one triangle. In this paper, we propose a randomized marking scheme to mark triangles and embed a feature filtering layer (FFL) in the pipeline of continuous collision detection. The purpose of the FFL is to extract potentially interacting feature pairs according to the marking of the triangles. By applying the FFL each interacting feature pair is processed exactly one time for the computation of collision information. On average, the number of potentially interacting feature pairs reduces significantly after filtering. We have integrated the FFL in a cloth simulation system. Interactive rates can be achieved for complex draping simulation.

Dynamic interaction between deformable surfaces and nonsmooth objects

In this paper, we introduce new techniques that enhance the computational performance for the interactions between sharp objects and deformable surfaces. The new formulation is based on a time-domain predictor-corrector model. For this purpose, we define a new kind of (pi, beta, I)-surface. The partitioning of a deformable surface into a finite set of (pi, beta, I)-surfaces allows us to prune a large number of noncolliding feature pairs. This leads to a significant performance improvement in the collision detection process. The intrinsic collision detection is performed in the time domain. Although it is more expensive compared to the static interference test, it avoids portions of the surfaces passing through each other in a single time step. In order to resolve all the possible collision events at a given time, a penetration-free motion space is constructed for each colliding particle. By keeping the velocity of each particle inside the motion space, we guarantee that the current colliding feature pairs will not penetrate each other in the subsequent motion. A static analysis approach is adopted to handle friction by considering the forces acting on the particles and their velocities. In our formulation, we further reduce the computational complexity by eliminating the need to compute repulsive forces.

Image-based collision detection for deformable cloth models

Modeling the natural interaction of cloth and garments with objects in a 3D environment is currently one of the most computationally demanding tasks. These highly deformable materials are subject to a very large number of contact points in the proximity of other moving objects. Furthermore, cloth objects often fold, roll, and drape within themselves, generating a large number of self-collision areas. The interactive requirements of 3D games and physically driven virtual environments make the cloth collisions and self-collision computations more challenging. By exploiting mathematically well-defined smoothness conditions over smaller patches of deformable surfaces and resorting to image-based collision detection tests, we developed an efficient collision detection method that achieves interactive rates while tracking self-interactions in highly deformable surfaces consisting of a large number of elements. The method makes use of a novel technique for dynamically generating a hierarchy of cloth bounding boxes in order to perform object-level culling and image-based intersection tests using conventional graphics hardware support. An efficient backward voxel-based AABB hierarchy method is proposed to handle deformable surfaces which are highly compressed.

RECODE: an image-based collision detection algorithm

Object interactions are ubiquitous in interactive computer graphics, 3D object motion simulations, virtual reality and robotics applications. Most collision detection algorithms are based on geometrical object space interference tests. Some algorithms have employed an image space approach to the collision detection problem. We demonstrate an image space collision detection process that allows substantial computational savings during the image space interference test. This approach makes efficient use of the graphics rendering hardware for real time complex object interactions.

Rendering in object interference detection on conventional graphics workstations

Collision detection between complex objects using rasterizing graphics hardware provides a rich ground of exploration for speeding up the interference detection algorithms and computing points of collision. We show that despite the limitations imposed by the current graphics rendering hardware, it is still possible to perform collision detection at rendering rates using only conventional graphics hardware without any enhancements.

Re-examining the effects of adding relevance information in a relevance feedback environment

This paper presents an investigation about how to automatically formulate effective queries using full or partial relevance information (i.e., the terms that are in relevant documents) in the context of relevance feedback (RF). The effects of adding relevance information in the RF environment are studied via controlled experiments. The conditions of these controlled experiments are formalized into a set of assumptions that form the framework of our study. This framework is called idealized relevance feedback (IRF) framework. In our IRF settings, we confirm the previous findings of relevance feedback studies. In addition, our experiments show that better retrieval effectiveness can be obtained when (i) we normalize the term weights by their ranks, (ii) we select weighted terms in the top K retrieved documents, (iii) we include terms in the initial title queries, and (iv) we use the best query sizes for each topic instead of the average best query size where they produce at most five percentage points improvement in the mean average precision (MAP) value. We have also achieved a new level of retrieval effectiveness which is about 55-60% MAP instead of 40+% in the previous findings. This new level of retrieval effectiveness was found to be similar to a level using a TREC ad hoc test collection that is about double the number of documents in the TREC-3 test collection used in previous works.

GPU‐based intrinsic collision detection for deformable surfaces

An intrinsic collision detection unit (ICDU) forms the bottom‐most layer of a collision detection pipeline. The ICDU performs collision detection and computes collision information for primitive feature pairs of objects in a 3D dynamic environment. A significant amount of time can be spent by the ICDU during the collision detection process. In this paper, we extend the ICDU framework to take advantages of the computational power of programmable graphics processors (GPUs). Some components of the ICDU framework consist of time demanding and fine‐grained tasks that can be implemented on GPUs. By employing the framework, collision information can be computed accurately, robustly, and efficiently. Experimental results show that the proposed method greatly improves the performance of the ICDU. A collection buffer is proposed for the future enhancement of GPU‐based collision detectors. Copyright