Real-time Character Research Articles

Dynamic obstacle avoidance for real-time character animation

This paper proposes a novel method to control virtual characters in dynamic environments. A virtual character is animated by a locomotion and jumping engine, enabling production of continuous parameterized motions. At any time during runtime, flat obstacles (e.g. a puddle of water) can be created and placed in front of a character. The method first decides whether the character is able to get around or jump over the obstacle. Then the motion parameters are accordingly modified. The transition from locomotion to jump is performed with an improved motion blending technique. While traditional blending approaches let the user choose the transition time and duration manually, our approach automatically controls transitions between motion patterns whose parameters are not known in advance. In addition, according to the animation context, blending operations are executed during a precise period of time to preserve specific physical properties. This ensures coherent movements over the parameter space of the original input motions. The initial locomotion type and speed are smoothly varied with respect to the required jump type and length. This variation is carefully computed in order to place the take-off foot as close to the created obstacle as possible.

Active Noise Control of a Moving Evaluation Point in One Dimensional Acoustic Field (3rd Report, Proposal of Time-delay Separation Method in the Secondary Path Identification)

Active noise control of a moving point has been examined in our previous papers. The feature of the model is that the transfer characteristics between the noise control source and the evaluation point (aimed noise reduction point) change with the movement of the evaluation point. Real time character identification algorithm have been introduced to handle the problem. However, the convergent algorithm used in the identification works effectively only when the system is stationary, and this is one of the reason that the identification accurcy decreases when the speed of the evaluation point increases. Besides, the evaluation point moves during the identification process of the calculation and it can cause discrepancy between identification results and the real system. We propose new technique where transfer characteristics are divided into time delay factor and main components. Once the characters are divided, the change of transfer characteristics caused by the movement appears mostly in time delay factor, and since it is the function of the location, it is easy to get the delay factor. Applying this idea, one can expect remarkable improvement in the identification. This method is examined numerically and experimentally in this paper.

Overview: Formation Evaluation (May 2005)

A new generation of downhole intelligent systems has made real-time reservoir evaluation the new norm in the industry. Advances in formation-evaluation tools, such as the modern capture and near-infrared spectroscopy tools, allowing more-accurate determination of petrophysical data and in-situ fluid composition, have matched the growing sophistication in geosteering and well placement through improved measurement-while-drilling and logging-while-drilling technologies. The emerging real-time character of formation evaluation brings along a host of new challenges for the industry. We need to ponder the answers to questions such as the following. - How do we manage the enormous growth in the volume of data? - How do we convert the extra data to higher-accuracy reservoir characterization? Fuzzy logic and neural networks may point to potential pathways. Another noteworthy evolution is occurring in the area of formation imaging. Spanning across many scales, ranging from the pore throat to the wellbore, new dual-energy computer-tomography-scanning and nuclear-magnetic-resonance mapping techniques enable us to peer inside the rock to get a better understanding of multiphase-flow experiments. Wells with vastly complex subsurface architectures give us the ability to image reservoirs (e.g., fractures, boundaries, and orientation frequency) in greater detail than ever before. In short, formation evaluation is getting better and smarter. Additional Formation Evaluation Technical Papers Available at the SPE eLibrary: www.spe.org SPE 88688 Image Enhancement, Automated Interpretation, and 3D Visualization of Borehole-Image Logs in Characterization and Calibration of Fractures in Kuwait SPE 88636 Design Considerations for a New High-Data-Rate LWD Acoustic Telemetry System SPE 88519 A Case Study of Carbon-Oxygen Logging Through Multiple Tubular Strings Offshore Indonesia: Reservoir-Model Verification With Emphasis on Fluid Contact and Bypass Oil Identification SPE 91607 Damage Interpretation of Properly and Improperly Drilled Underbalanced Horizontals in the Fractured Jean Marie Reservoir Using Novel Modeling and Methodology

Level-of-detail for cognitive real-time characters

We present a solution for the real-time simulation of artificial environments containing cognitive and hierarchically organized agents at constant rendering framerates. We introduce a level-of-detail concept to behavioral modeling, where agents populating the world can be both reactive and proactive. The disposable time per rendered frame for behavioral simulation is variable and determines the complexity of the presented behavior. A special scheduling algorithm distributes this time to the agents depending on their level-of-detail such that visible and nearby agents get more time than invisible or distant agents. This allows for smooth transitions between reactive and proactive behavior. The time available per agent influences the proactive behavior, which becomes more sophisticated because it can spend time anticipating future situations. Additionally, we exploit the use of hierarchies within groups of agents that allow for different levels of control. We show that our approach is well-suited for simulating environments with up to several hundred agents with reasonable response times and the behavior adapts to the current viewpoint.

Adapting motion capture data using weighted real-time inverse kinematics

In this article we present a technique that enhances an inverse kinematics (IK) solver such that when the results are applied to a computer character, we can generate a level of individualization tailored to both the character and the environment, e.g., a walking motion can become "stiffer" or can be turned into a limping motion. Since the technique is based on an IK solver, we also have the desirable effect of solving retargetting issues when mapping motion data between characters. As the individualization aspect of our technique is very tightly coupled with the inverse kinematics solver, we can achieve both the individualization and retargetting of characters in real time.

Fast and learnable behavioral and cognitive modeling for virtual character animation

AbstractBehavioral and cognitive modeling for virtual characters is a promising field. It significantly reduces the workload on the animator, allowing characters to act autonomously in a believable fashion. It also makes interactivity between humans and virtual characters more practical than ever before. In this paper we present a novel technique where an artificial neural network is used to approximate a cognitive model. This allows us to execute the model much more quickly, making cognitively empowered characters more practical for interactive applications. Through this approach, we can animate several thousand intelligent characters in real time on a PC. We also present a novel technique for how a virtual character, instead of using an explicit model supplied by the user, can automatically learn an unknown behavioral/cognitive model by itself through reinforcement learning. The ability to learn without an explicit model appears promising for helping behavioral and cognitive modeling become more broadly accepted and used in the computer graphics community, as it can further reduce the workload on the animator. Further, it provides solutions for problems that cannot easily be modeled explicitly. Copyright © 2004 John Wiley & Sons, Ltd.

Modeling and solving real-time scheduling problems by stochastic integer programming

This contribution deals with scheduling problems of flexible chemical batch processes with a special emphasis on their real-time character. This implies not only the need for sufficiently short response times, but in particular the burden of in-complete knowledge about the future. To solve such problems, the application of two-stage stochastic integer programming techniques on moving horizons is proposed. They reflect the need for immediately applicable decisions and the potential of later recourse actions to cope with realized uncertainties. In addition to the classical expected value objective, simple measures of risk can be included. Motivated by an example process, some essential modeling prerequisites are discussed. As an important first step, the master scheduling problem is studied and a number of master scheduling models are presented. Large mixed-integer linear problems arise, which are well-suited for a dual decomposition approach. Numerical experiments with a problem-specific solution algorithm demonstrate the applicability of the method to real-world problems.

Near real-time geocoding of SAR imagery with orbit error removal

When utilizing knowledge of the spacecraft trajectory for near real-time geocoding of Synthetic Aperture Radar (SAR) images, the main problem is that predicted satellite orbits have to be used, which may be in error by several kilometres. As part of the development of a Dutch autonomous mobile ground station to receive and process satellite SAR data, a method has been developed that removes the effects of orbit errors from the computed azimuth and slant-range coordinates, whilst maintaining the real-time character. Results show that predicted orbits can be used to geocode SAR imagery in near real time with the same accuracy as when using precise orbits, i.e. 30–40m.

On the trail of the shadow woman: the mystery of motion capture

Motion capture houses throw away the person and keep the shadow-the essence of their motion-and apply that motion to animate all kinds of characters. In the past few years, as the technology has become less expensive and at the same time more accurate, MoCap has helped lessen the rigors of traditional cell animation-especially in highly cost-conscious projects like TV commercials. A MoCap studio can use both magnetic and optical capture systems. Each has certain advantages. The magnetic system handles shoots that don't need really high accuracy, and the director wants to be able to apply the data to his character in real time. Magnetic systems generally are faster at providing data to use in animation, though optical systems are generally more accurate and can track more points. That may be changing, though.

Tracking and Motion Estimation of the Articulated Object: a Hierarchical Kalman Filter Approach

Real-time motion capture plays a very important role in various applications, such as 3D interface for virtual reality systems, digital puppetry, and real-time character animation. In this paper we challenge the problem of estimating and recognizing the motion of articulated objects using theoptical motion capturetechnique. In addition, we present an effective method to control the articulated human figure in realtime.The heart of this problem is the estimation of 3D motion and posture of an articulated, volumetric object using feature points from a sequence of multiple perspective views. Under some moderate assumptions such as smooth motion and known initial posture, we develop a model-based technique for the recovery of the 3D location and motion of a rigid object using a variation of Kalman filter. The posture of the 3D volumatric model is updated by the 2D image flow of the feature points for all views. Two novel concepts – the hierarchical Kalman filter (KHF) and the adaptive hierarchical structure (AHS) incorporating the kinematic properties of the articulated object – are proposed to extend our formulation for the rigid object to the articulated one. Our formulation also allows us to avoid two classic problems in 3D tracking: the multi-view correspondence problem, and the occlusion problem. By adding more cameras and placing them appropriately, our approach can deal with the motion of the object in a very wide area. Furthermore, multiple objects can be handled by managing multiple AHSs and processing multiple HKFs.We show the validity of our approach using the synthetic data acquired simultaneously from the multiple virtual camera in a virtual environment (VE) and real data derived from a moving light display with walking motion. The results confirm that the model-based algorithm works well on the tracking of multiple rigid objects.

A unit decomposition technique using fuzzy logic for real-time handwritten Chinese character recognition

The purpose of this paper is to provide a real-time compact device for inputting handwritten characters to mobile personal digital assistants (PDAs). A novel method for the recognition of online handwritten Chinese characters is presented, giving emphasis to the representation of the patterns using fuzzy logic. The information contained in a character, including shapes of individual strokes and their relative spatial relations, is examined by inference of fuzzy rule base, and the fuzzified representation is organized in a matrix structure. It is well known that Chinese characters are comprised of a set of basic units, representing fundamental meanings. Hence, a unit extraction module is designed to search the possible units within characters. The input character object is recognized by a combination of units with the largest fuzzy confidence degree. The training capability, which provides the unit model set, is performed using the qualitative fuzzy c-means clustering algorithm. An experimental system is implemented that achieves a real-time recognition rate of about 95% with a test set of 550 characters and two cases for each character written by six users. The experimental system has an average real-time recognition speed of 0.5 s/character. The presented approach shows the following two significant advantages over other methods: (1) less training time; and (2) less storage required to store character models. These are two crucial factors in designing PDA devices for mobile communication.

Conjugate Image Plane Correlator with Holographic Disk Memory

A conjugate image plane correlator with holographic disk memory is proposed. Optical correlation between conjugate images reconstructed from a holographic disk and an input image on liquid-crystal television is executed with the rotation of the disk. Regardless of Fourier hologram recording with the pseudorandom diffuser, it is found possible to take out the diffuser from the original hologram recording scheme using an image reconstruction process and to get correlation signals between input and reconstructed conjugate images in the output plane of a two-lens imaging system. Generation of conjugate replicas with high contrast causes exact matching with an input image which results in high recognition performance for autocorrelation signals. The transfer function of an optical system can be controlled by adjustment of either hologram size or hologram area illuminated with a laser beam. Hence, the output intensity distribution can be adjusted by selecting a proper pupil function and the size of an output pupil defined by the input pupil size and the optical system magnification factor. The real-time character recognition by optical parallel high-speed processing for two dimensional images with position normalization is demonstrated.

Feature-extracted joint transform correlation

A new technique for real-time optical character recognition that uses a joint transform correlator is proposed. This technique employs feature-extracted patterns for the reference image to detect a wide range of characters in one step. The proposed technique significantly enhances the processing speed when compared with the presently available joint transform correlator architectures and shows feasibility for multichannel joint transform correlation.

Real time character scaling and rotation

This paper describes a real time signal processing subsystem used to perform character scaling and rotation. First, the algorithms used in the subsystem are described. The algorithms were developed for performing sorting decisions on mail for the USPS. The computational complexity of the algorithms implemented in the subsystem is then reviewed, and finally the implementation of the algorithms in discrete logic, DSP's, and FPGA's is discussed.

Real time responsive animation with personality

Building on principles from prior work on procedural synthesis (K. Perlin, 1985), we are able to create remarkably lifelike, responsively animated characters in real time. Rhythmic and stochastic noise functions are used to define time varying parameters that drive computer generated puppets. Because we are conveying just the texture of motion, we are able to avoid computation of dynamics and constraint solvers. The subjective impression of dynamics and other subtle influences on motion can be conveyed with great visual realism by properly tuned expressions containing pseudo random noise functions. For example, we can make a character appear to be dynamically balancing herself, to appear nervous, or to be gesturing in a particular way. Each move has an internal rhythm, and transitions between moves are temporally constrained so that impossible transitions are precluded. For example, if while the character is walking we specify a dance turn, the character will always step into the turn onto the correct weight bearing foot. An operator can make a character perform a properly connected sequence of actions, while conveying particular moods and attitudes, merely by pushing buttons at a high level. Potential uses of such high level textural approaches to computer graphic simulation include role playing games, simulated conferences, clip animation, graphical front ends for MUDs, and synthetic performances. >

STUDIES OF THE REAL-TIME OPTICAL CORRELATION STORAGE IN LiNbO3:Fe Photorefractive Crystals

The real-time optical correlation-storage in photorefractive crystals has firstly been realized. It possesses the advantages of both storage and correlator, as well as the real-time character of photorefractive devices. It can performa real-time and fast selection of imformation correlated to the input ones from a great amount of stored imformation. The correlation degree of every information with the input ones and its coding number are immediately obtained from the intensity and position of the correlation points. This principle is based on the selectivity of photorefractive matched filter. Hence this device has wide prospect of application.

An Adaptive Opto-electronic Neural Network for Associative Pattern Retrieval

A novel adaptive trinary neural network model is proposed for associative pattern retrieval from incomplete data. Systematic analysis of the convergence mechanism for the character recognition problem is provided to illustrate the derivation of this novel adaptive thresholding scheme. The adaptive scheme with trinary input representation outperforms other associative retrieval schemes in terms of convergence and storage capacity. The inherent parallelism of this neural network architecture is exploited for a parallel optical implementation. The tremendous speed and free-space interconnection capability of optics results in a very efficient real-time character recognition system. The adaptive threshold scheme developed here may have far reaching implications for other neural networks in enhancing their learning and retrieval, speed, and accuracy.

Visualization and Measurement of Slope and Curvature Fields Using Holographic Interferometry: An Application to Flaw Detection

Abstract This paper reports the application of wave-front shearing and phase shifting to holographic interferometry in order to obtain whole field phase maps corresponding to slope and curvature distributions. A theoretical analysis of fringe formation is presented and interferometers to implement the method are proposed. The real-time character of the method is mostly kept intact. Experimental results are presented to illustrate the feasibility of the technique. The application equally demonstrates the usefulness of the method in flaw detection.

A neural network-based on-line Chinese character recognition system

A neural network-based on-line Chinese character recognition (OLCCR) system is presented. In this paper, a back-propagation neural network model is proposed for solving the pattern-matching problems in OLCCR, instead of those non-neural network-based algorithms. This OLCCR system will enable us to recognize handwritten Chinese characters in real time. Each recognition process includes two main phases: (A) the feature-extraction phase, in which a feature vector based on reference stroke information can be extracted, and (B) the character-matching phase, in which the feature vector is matched with a group of standard Chinese reference character feature vectors. Experimental results show that it takes about 0.25 s to recognize a handwritten character and that a recognition rate of about 91% can be achieved.

Progress in fieldbus developments for measuring and control applications

Abstract Digital communication is widely used for process supervisory networks. Some digital communication is beginning to penetrate to the process field, e.g., smart transmitter communication. Future communications will be of real-time character. Fieldbus is such a communication link. Extensive work has been done on fieldbus in projects and in standardization groups. The PROFIBUS project created the DIN 19245 standard, and the factory information protocol (FIP) project created the NF C46-60X standard. International work is also being done in IEC SC65C WG6. The first secretariat documents exist for requirements and the physical layer. The time schedule plans that draft documents for physical and link layers will be ready in 1991 and for the application layer in 1992.