George Baciu

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.

Template-based generation of road networks for virtual city modeling

In modern urban areas, we often find a transportation network that follows a superimposed pattern. In this paper, we propose a novel method to generate a virtual traffic network based on (1) image-derived templates, and (2) a rule-based generating system. Using 2D images as input maps, various road maps with different patterns could be produced. This traffic network generating model adjusts itself intelligently in order to avoid restricted geographical areas or urban developments. The generative model follows closely directions of elevation and connects road ends in ways that allow various types of breakpoints.

Using Wi-Fi Signal Strength to Localize in Wireless Sensor Networks

Wireless sensor network (WSN) is widely used in many applications such as localization and real-time tracking system. Previous researches commonly suffer the line-of-sight (LOS) problem and dependence on contrast of the background light intensity. Location Fingerprinting (LF) method uses a training dataset of received signal strength (RSS) at different location to track the target. The drawbacks of LF method are needed to have extensive training dataset surveying and highly affected by the changing of internal building infrastructure. In this paper, a sensor-based LF method will be implemented to replace extensive site-surveying. Using a Kalman Filter tracks multiple points to characterize a trajectory. Our experimental result shows that the effectiveness of our method leads to have more accurate and effective tracking system.

Investigation on the Classification of Weave Pattern Based on an Active Grid Model

In this paper, a new method based on the active grid model (AGM) is used to identify the weave pattern of woven fabrics. The two-dimensional geometrical weaving structure of the woven fabrics could be described mathematically using the concept of active grid alignment, so that the analysis of the fabric weave pattern could be implemented in the field of an AGM model of a fabric. This proposed method utilizes dual-side scanning technology to merge the dual-side images of a fabric at the yarn level. It contains a four-step method to construct an AGM. First, a yarn-detecting algorithm is applied on the dual-side scan images to initialize the AGM. Second, the AGM self-adjustment scheme is used to adjust the AGM accurately. Then, the types of the yarn interlacing are classified based on the edge map and the result is refined using the neighboring information of yarns. Finally, the color pattern is determined by using color clustering and matching; error correction is also made based on the color configuration. Some preliminary experiments show that the AGM is effective for the classification of fabric weaving patterns.

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.

Nonconvex sparse regularizer based speckle noise removal

This paper focuses on the problem of speckle noise removal. A new variational model is proposed for this task. In the model, a nonconvex regularizer rather than the classical convex total variation is used to preserve edges/details of images. The advantage of the nonconvex regularizer is pointed out in the sparse framework. In order to solve the model, a new fast iteration algorithm is designed. In the algorithm, to overcome the disadvantage of the nonconvexity of the model, both the augmented Lagrange multiplier method and the iteratively reweighted method are introduced to resolve the original nonconvex problem into several convex ones. From the algorithm, we can obtain restored images as well as edge indicator of the images. Comprehensive experiments are conducted to measure the performance of the algorithm in terms of visual evaluation and a variety of quantitative indices for the task of speckle noise removal.

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.