We present a novel paradigm for pattern matching. Our method provides a means to search a continuous data stream for exact matches with a priori stored data sequences. At heart, we use a neural network with input and output layers and variable connections in between. The input layer has one neuron for each possible character or number in the data stream, and the output layer has one neuron for each stored pattern. The novelty of the network is that the delays of the connections from input to output layer are optimized to match the temporal occurrence of an input character within a stored sequence. Thus, the polychronous activation of input neurons results in activating an output neuron that indicates detection of a stored pattern. For data streams that have a large alphabet, the connectivity in our network is very sparse and the number of computational steps small: in this case, our method outperforms by a factor 2 deterministic finite state machines, which have been the state of the art for pattern matching for more than 30 years.

We describe and evaluate a new tracking concept for outdoor Augmented Reality. A few mobile beacons added to the environment correct errors in head-worn inertial and GPS sensors. We evaluate the accuracy through detailed simulation of many error sources. The most important parameters are the errors in measuring the beacon and user's head positions, and the geometric configuration of the beacons around the point to augment. Using Monte Carlo simulations, we identify combinations of beacon configurations and error parameters that meet a specified goal of 1 m net error at 100 m range.

This paper describes a 2D videoconferencing system with eye gaze correction. Tracking the eyes and warping the eyes appropriately each frame appears to create natural eye contact between users. The geometry of the eyes as well as the displacement of the camera with the remote user's image determines the warp. We implement this system within software, not requiring any specialized hardware.

One unique feature of mixed and augmented reality (MR/AR) systems is that hidden and occluded objects an be readily visualized. We call this specialized use of MR/AR, obscured information visualization (OIV). In this paper, we describe the beginning of a research program designed to develop such visualizations through the use of principles derived from perceptual psychology and cognitive science. In this paper we surveyed the cognitive science literature as it applies to such visualization tasks, described experimental questions derived from these cognitive principles, and generated general guidelines that can be used in designing future OIV systems (as well improving AR displays more generally). We also report the results from an experiment that utilized a functioning AR-OIV system: we found that in relative depth judgment, subjects reported rendered objects as being in front of real-world objects, except when additional occlusion and motion cues were presented together.

"Free Flight" will change today's air traffic control system by giving pilots increased flexibility to choose and modify their routes in real time, reducing costs and increasing system capacity. This increased flexibility comes at the price of increased complexity. If Free Flight is to become a reality, future air traffic controllers, pilots, and airline managers will require new conflict detection, resolution and visualization decision support tools. The paper describes a testbed system for building and evaluating such tools, including its current capabilities, lessons we learned and feedback received from expert users. The visualization system provides an overall plan view supplemented with a detailed perspective view, allowing a user to examine highlighted conflicts and select from a list of proposed solutions, as the scenario runs in real time. Future steps needed to improve this system are described.

The use of Markov random fields (MRFs) in color image segmentation of natural outdoor scenes is discussed. MRFs provide an elegant means of specifying a local energy function which embodies the expected dependencies of neighboring pixels and includes both the prior and posterior probabilistic distributions. This local neighborhood-based specification of dependencies avoids ad hoc brittle methods using global image knowledge. A brief analysis of ongoing research in color differencing methods is presented, since they are central to the problem of color segmentation. The authors develop and compare the use of three different lattice structures for coupled MRFs with line and color processes based on squares, hexagons, and triangles, and also discusses current efforts in MRF parameter understanding.>

The authors present an operational perception system for cross-country navigation which has been verified in both simulated and real-world environments. Range data from a laser range scanner is transformed into an alternate representation called the Cartesian elevation map (CEM). A detailed vehicle model operates on the CEM to produce traversability information along selected trajectories. This information supports a real-time reflexive planning system. The authors successfully demonstrated their obstacle detection and avoidance algorithms on board the autonomous land vehicle at Martin Marietta Aerospace Corporation in Denver. They also propose enhancements to their current operational system.>

A description is given of the first cross-country map and sensor-based autonomous operation of a robotic vehicle. Experiments on the autonomous land vehicle (ALV) in natural terrain were performed. An overview of the software architecture is provided, and details of the perception and planning techniques are presented. Two key experiments in which the vehicle avoided known and unknown obstacles in its path are described.>