Automatic high-resolution optoelectronic photogrammetric 3D surface geometry acquisition system

A fast, high-resolution, automatic, non-contact 3D surface geometry measuring system using a photogrammetric optoelectronic technique based on lateral-photoeffect diode detectors has been developed. Designed for the acquisition of surface geometries such as machined surfaces, biological surfaces, and deformed parts, the system can be used in design, manufacturing, inspection, and range finding. A laser beam is focused and scanned onto the surface of the object to be measured. Two cameras in stereo positions capture the reflected light from the surface at 10 kHz. Photogrammetric triangulation quickly transforms the pair of 2D signals created by the camera detectors into 3D coordinates of the light spot. Because only one small spot on the object is illuminated at a time, the stereo correspondence problem is solved in real time. The resolution is determined by a 12-bit A/D converter and can be improved up to 25 60025 600 by oversampling. The irregular 3D data can be regularized for use with image-based algorithms. Received: 8 October 1996 / Accepted: 3 February 1997     

Efficient similarity search for market basket data

Several organizations have developed very large market basket databases for the maintenance of customer transactions. New applications, e.g., Web recommendation systems, present the requirement for processing similarity queries in market basket databases. In this paper, we propose a novel scheme for similarity search queries in basket data. We develop a new representation method, which, in contrast to existing approaches, is proven to provide correct results. New algorithms are proposed for the processing of similarity queries. Extensive experimental results, for a variety of factors, illustrate the superiority of the proposed scheme over the state-of-the-art method. Edited by R. Ng. Received: August 6, 2001 / Accepted: May 21, 2002 Published online: September 25, 2002     

Optimistic parallel Delaunay triangulation

The paper describes a new parallel algorithm of Delaunay triangulation based on randomized incremental insertion. The algorithm is practical, simple and can be modified also for constrained triangulation or tetrahedralization. It was developed for architectures with a lower degree of parallelism, such as several-processor workstations, and tested on up to 8 processors. Published online: November 20, 2002 This work was supported by the Ministry of Education of The Czech Republic, project MSM 235 200 005     

Parameterization for reconstruction of 3D freeform objects from laser-scanned data based on a PDE method

Published online: 19 July 2001     

Indexing of now-relative spatio-bitemporal data

Real-world entities are inherently spatially and temporally referenced, and database applications increasingly exploit databases that record the past, present, and anticipated future locations of entities, e.g., the residences of customers obtained by the geo-coding of addresses. Indices that efficiently support queries on the spatio-temporal extents of such entities are needed. However, past indexing research has progressed in largely separate spatial and temporal streams. Adding time dimensions to spatial indices, as if time were a spatial dimension, neither supports nor exploits the special properties of time. On the other hand, temporal indices are generally not amenable to extension with spatial dimensions. This paper proposes the first efficient and versatile index for a general class of spatio-temporal data: the discretely changing spatial aspect of an object may be a point or may have an extent; both transaction time and valid time are supported, and a generalized notion of the current time, now, is accommodated for both temporal dimensions. The index is based on the R-tree and provides means of prioritizing space versus time, which enables it to adapt to spatially and temporally restrictive queries. Performance experiments are reported that evaluate pertinent aspects of the index. Edited by T. Sellis. Received: 7 December 2000 / Accepted: 1 September 2001 Published online: 18 December 2001     

Efficient collision detection for models deformed by morphing

Published online: 5 February 2003     

Intelligent multimedia data: data + indices + inference

In this paper, we present a novel approach for multimedia data indexing and retrieval that is machine independent and highly flexible for sharing multimedia data across applications. Traditional multimedia data indexing and retrieval problems have been attacked using the central data server as the main focus, and most of the indexing and query-processing for retrieval are highly application dependent. This precludes the use of created indices and query processing mechanisms for multimedia data which, in general, have a wide variety of uses across applications. The approach proposed in this paper addresses three issues: 1. multimedia data indexing; 2. inference or query processing; and 3. combining indices and inference or query mechanism with the data to facilitate machine independence in retrieval and query processing. We emphasize the third issue, as typically multimedia data are huge in size and requires intra-data indexing. We describe how the proposed approach addresses various problems faced by the application developers in indexing and retrieval of multimedia data. Finally, we present two applications developed based on the proposed approach: video indexing; and video content authorization for presentation.     

Spatial indexing of high-dimensional data based on relative approximation

We propose a novel index structure, the A-tree (approximation tree), for similarity searches in high-dimensional data. The basic idea of the A-tree is the introduction of virtual bounding rectangles (VBRs) which contain and approximate MBRs or data objects. VBRs can be represented quite compactly and thus affect the tree configuration both quantitatively and qualitatively. First, since tree nodes can contain a large number of VBR entries, fanout becomes large, which increases search speed. More importantly, we have a free hand in arranging MBRs and VBRs in the tree nodes. Each A-tree node contains an MBR and its children VBRs. Therefore, by fetching an A-tree node, we can obtain information on the exact position of a parent MBR and the approximate position of its children. We have performed experiments using both synthetic and real data sets. For the real data sets, the A-tree outperforms the SR-tree and the VA-file in all dimensionalities up to 64 dimensions, which is the highest dimension in our experiments. Additionally, we propose a cost model for the A-tree. We verify the validity of the cost model for synthetic and real data sets. Edited by T. Sellis. Received: December 8, 2000 / Accepted: March 20, 2002 Published online: September 25, 2002     

Robust online detection of pipeline corrosion from range data

We present the Finite-Window Robust Sequential Estimator for the detection and analysis of corrosion in range images of gas pipelines. This statistically robust, real-time technique estimates the pipeline surface range function in the presence of noise, surface deviations, and changes in the underlying model. Deviations from the robust surface fit, corresponding to statistical outliers, represent potential areas of corrosion. Because the algorithm estimates surface parameters over a finite, sliding window of data, it can track moderately high-order surfaces using lower order models. The system is consistent, objective, and non-destructive and can be used with the pipeline in service. Received: 7 September 1999 / Accepted: 2 November 2000     

Simulation of postoperative 3D facial morphology using a physics-based head model

We propose a prototype of a facial surgery simulation system for surgical planning and the prediction of facial deformation. We use a physics-based human head model. Our head model has a 3D hierarchical structure that consists of soft tissue and the skull, constructed from the exact 3D CT patient data. Anatomic points measured on X-ray images from both frontal and side views are used to fire the model to the patient's head. The purposes of this research is to analyze the relationship between changes of mandibular position and facial morphology after orthognathic surgery, and to simulate the exact postoperative 3D facial shape. In the experiment, we used our model to predict the facial shape after surgery for patients with mandibular prognathism. Comparing the simulation results and the actual facial images after the surgery shows that the proposed method is practical.     

Geometric fusion for a hand-held 3D sensor

Abstract. This article presents a geometric fusion algorithm developed for the reconstruction of 3D surface models from hand-held sensor data. Hand-held systems allow full 3D movement of the sensor to capture the shape of complex objects. Techniques previously developed for reconstruction from conventional 2.5D range image data cannot be applied to hand-held sensor data. A geometric fusion algorithm is introduced to integrate the measured 3D points from a hand-held sensor into a single continuous surface. The new geometric fusion algorithm is based on the normal-volume representation of a triangle, which enables incremental transformation of an arbitrary mesh into an implicit volumetric field function. This system is demonstrated for reconstruction of surface models from both hand-held sensor data and conventional 2.5D range images. Received: 30 August 1999 / Accepted: 21 January 2000     

Clustering categorical data: an approach based on dynamical systems

We describe a novel approach for clustering collections of sets, and its application to the analysis and mining of categorical data. By “categorical data,” we mean tables with fields that cannot be naturally ordered by a metric – e.g., the names of producers of automobiles, or the names of products offered by a manufacturer. Our approach is based on an iterative method for assigning and propagating weights on the categorical values in a table; this facilitates a type of similarity measure arising from the co-occurrence of values in the dataset. Our techniques can be studied analytically in terms of certain types of non-linear dynamical systems. Received February 15, 1999 / Accepted August 15, 1999     

Using vanishing points for camera calibration and coarse 3D reconstruction from a single image

In this paper, we show how to calibrate a camera and to recover the geometry and the photometry (textures) of objects from a single image. The aim of this work is to make it possible walkthrough and augment reality in a 3D model reconstructed from a single image. The calibration step does not need any calibration target and makes only four assumptions: (1) the single image contains at least two vanishing points, (2) the length (in 3D space) of one line segment (for determining the translation vector) in the image is known, (3) the principle point is the center of the image, and (4) the aspect ratio is fixed by the user. Each vanishing point is determined from a set of parallel lines. These vanishing points help determine a 3D world coordinate system R _o. After having computed the focal length, the rotation matrix and the translation vector are evaluated in turn for describing the rigid motion between R _o and the camera coordinate system R _c. Next, the reconstruction step consists in placing, rotating, scaling, and translating a rectangular 3D box that must fit at best with the potential objects within the scene as seen through the single image. With each face of a rectangular box, a texture that may contain holes due to invisible parts of certain objects is assigned. We show how the textures are extracted and how these holes are located and filled. Our method has been applied to various real images (pictures scanned from books, photographs) and synthetic images.     

Energy-performance trade-offs for spatial access methods on memory-resident data

The proliferation of mobile and pervasive computing devices has brought energy constraints into the limelight. Energy-conscious design is important at all levels of system architecture, and the software has a key role to play in conserving battery energy on these devices. With the increasing popularity of spatial database applications, and their anticipated deployment on mobile devices (such as road atlases and GPS-based applications), it is critical to examine the energy implications of spatial data storage and access methods for memory resident datasets. While there has been extensive prior research on spatial access methods on resource-rich environments, this is, perhaps, the first study to examine their suitability for resource-constrained environments. Using a detailed cycle-accurate energy estimation framework and four different datasets, this paper examines the pros and cons of three previously proposed spatial indexing alternatives from both the energy and performance angles. Specifically, the Quadtree, Packed R-tree, and Buddy-Tree structures are evaluated and compared with a brute-force approach that does not use an index. The results show that there are both performance and energy trade-offs between the indexing schemes for the different queries. The nature of the query also plays an important role in determining the energy-performance trade-offs. Further, technological trends and architectural enhancements are influencing factors on the relative behavior of the index structures. The work in the query has a bearing on how and where (on a mobile client or/and on a server) it should be performed for performance and energy savings. The results from this study will be beneficial for the design and implementation of embedded spatial databases, accelerating their deployment on numerous mobile devices. Received: November 11, 2001 / Accepted: March 12, 2002 Published online: November 14, 2002 This paper is a significantly extended version of preliminary work that appeared in the Proceedings of the Very Large Databases (VLDB) 2001 Conference. The extensions include (i) a comparison of indexing alternatives carrying out the operations in a brute-force manner; (ii) observations showing that datasets do play a role in power consumption; (iii) architectural solutions to address the cache and memory hotspots for energy; and (iv) benefits when off-loading the work to a server over a wireless medium compared to doing everything on the handheld device.     

Automatic reconstruction of 3D human arm motion from a monocular image sequence

A model-based approach to reconstruction of 3D human arm motion from a monocular image sequence taken under orthographic projection is presented. The reconstruction is divided into two stages. First, a 2D shape model is used to track the arm silhouettes and second-order curves are used to model the arm based on an iteratively reweighted least square method. As a result, 2D stick figures are extracted. In the second stage, the stick figures are backprojected into the scene. 3D postures are reconstructed using the constraints of a 3D kinematic model of the human arm. The motion of the arm is then derived as a transition between the arm postures. Applications of these results are foreseen in the analysis of human motion patterns. Received: 26 January 1996 / Accepted: 17 July 1997     

Using 3D Sound to Improve the Effectiveness of the Advanced Driver Assistance Systems

Future generation cars will be characterized by a wide range of Information Technology (IT) services providing safety and infotainment. This makes the car an information intensive environment where the visual channel is overloaded, putting the safety of drivers and passengers in jeopardy. We propose the use of a 3D auditory display to provide information from the Advanced Driver Assistance Systems. This reduces the eye-off-road time, exploiting the human capability to associate sounds with positions in space. Preliminary lab tests reveal the suitability of this approach. The system still has to be carefully tuned and personalized to achieve usability and reliability, but we think that it provides a complementary channel that is specially useful in low visibility conditions.