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The article presents the partitioning method for providing latency to users in distributed virtual environment systems. The system throughput is maximized and receives satisfactory latency for providing quality service.

Real-time human-computer interaction plays an important role in virtual-environment (VE) applications. Such interaction can be improved by detecting and reacting to the user's head motion. Today's VE systems use head-mounted inertial sensors to update and spatially stabilize the image displayed to a user through a head-mounted display. Since motion can only be detected after it has already occurred, latencies in the stabilization scheme can only be reduced but never eliminated. Such latencies slow down manual control, cause inaccuracies in matching real and virtual objects through a half-transparent display, and reduce the sense of presence. This paper presents novel methods for reducing VE latencies by anticipating future head motion based on electromyographic (EMG) signals originating from the major neck muscles and head kinematics; it also reports results for anticipation of 17.5 and 35 ms. Features extracted from the EMG signals are used to train a neural network in mapping EMG data, given present head kinematics, into future head motion. The trained network is then used in real time for head-motion anticipation, which gives the VE system the time advantage necessary to compensate for the inherent latencies. The main contribution of this work is the use of EMG energy and bounded head acceleration as the key input/output information, which results in improved performance compared to the previous work. Index Terms--Electromyogram, head-mounted display, neural networks, pattern recognition, virtual environment.

Virtual reality techniques are now more and more widely used in the field of surgical training. However, the realism of the simulation devices requires a good knowledge of the mechanical behavior of the living organs. To provide perioperative measurement of laparoscopic surgical operations, we equipped a conventional operating grasper with a force sensor and a position sensor. The entire apparatus was connected to a PC that controlled the real-time data acquisition. After calibrating the sensors, we conducted three series of in vivo measurements on animals under video control. A standardized protocol was set up to perform various surgical gestures in a reproducible manner. Under these conditions, we can assess an original tool for a quantitative approach of surgical gestures' mechanics. The preliminary results will be extended by measurements during other operations and with other surgical instruments. The in vivo quantification of the mechanical interactions between operating instruments and anatomical structures is of great interest for the introduction of the force feedback in virtual surgery, for the modeling of the mechanical behavior of living organs, and for the design of new surgical instruments. This quantification of manipulations opens new prospects in the evaluation of surgical practices. Index Terms--Biomechanics, in vivo measurements, surgical gestures.

Modern video-based endoscopes offer physicians a wide-angle field of view (FOV) for minimally invasive procedures. Unfortunately, inherent barrel distortion prevents accurate perception of range. This makes measurement and distance judgment difficult and causes difficulties in emerging applications, such as virtual guidance of endoscopic procedures. Such distortion also arises in other wide FOV camera circumstances. This paper presents a distortion-correction technique that can automatically calculate correction parameters, without precise knowledge of horizontal and vertical orientation. The method is applicable to any camera-distortion correction situation. Based on a least-squares estimation, our proposed algorithm considers line fits in both FOV directions and gives a globally consistent set of expansion coefficients and an optimal image center. The method is insensitive to the initial orientation of the endoscope and provides more exhaustive FOV correction than previously proposed algorithms. The distortion--correction procedure is demonstrated for endoscopic video images of a calibration test pattern, a rubber bronchial training device, and real human circumstances. The distortion correction is also shown as a necessary component of an image-guided virtual-endoscopy system that matches endoscope images to corresponding rendered three-dimensional computed tomography views. Index Terms--Barrel distortion, camera calibration, distortion correction, endoscopy, image-guided endoscopy, virtual endoscopy.

This article describes the design and implementation of a virtual laboratory, computer-generated for the theoretical and practical teaching of electronic instrumentation. The virtual laboratory is implemented in a windows framework for which the teacher or student requires no prior knowledge to manage the program. The Virtual Instrumentation Workbench for Instrumentation allows visualization of the time and frequency effects produced in analog to digital conversion and in digital signal processing as well as visualizing the effects of 16 different teaching topics. It incorporates ten different waveforms, eight windows algorithms, five digital filters, and five discrete/fast Fourier transform (DFT/FFT). The use of the virtual laboratory has allowed more than 500 students to understand the functioning of the new devices that are flooding the instrumentation market. Although it has been developed as an aid for electronic instrumentation teaching, it can also be used for the teaching of digital signal treatment.