Surface Registration at 10Hz Based on Landmark-Graphs: Benefits for a Scalable Remote Viewing System

Real-time surface registration is a key technology for the development of future remote viewing systems. An architecture for a video distribution system supporting multiple users, with individual viewpoint selection, is suggested. The approach would provide a transmission bandwidth independent of the number of users, for scalability. The proposed architecture uses a method of surface registration based on landmark-graphs. Results from 141 test trials on synthetic scenes indicate that a mean absolute positioning accuracy under 1% of the sensor field of view is possible. The mean rate for registration was 10Hz, with a standard deviation under 10%. Tests were benchmarked on a 900MHz PC. The sensor images were 200x200 pixels and contained both range and color imagery

Structural Matching Via Optimal Basis Graphs

The ‘basis graph’ approach to structural matching uses a fixed set of small (4 node) graphs to characterize local structure. We compute mapping probabilities by first finding the probability of a basis graph being an induced subgraph of the input graph. The similarity of these probabilities is used to compare nodes of the input graphs. The method permits common subgraphs to be identified without the use of any node or edge coloring. We report on an improved, simpler, version of the algorithm, which has also been optimized. Performance is compared with the LeRP method, which is based on length-r paths. Both methods are approximate with polynomial bounds on both memory and on the worst-case compute effort. These methods work on arbitrary types of undirected graphs, and tests with strongly regular graphs are included. Monte Carlo test trials (3000+) included up to 100% additional (noise) nodes

Reduced Bandwidth for Remote Vehicle Operations

Oak Ridge National Laboratory staff have developed a video compression system for low-bandwidth remote operations. The objective is to provide real-time video at data rates comparable to available tactical radio links, typically 16 to 64 thousand bits per second (kbps), while maintaining sufficient quality to achieve mission objectives. The system supports both continuous lossy transmission of black and white (gray scale) video for remote driving and progressive lossless transmission of black and white images for remote automatic target acquisition. The average data rate of the resulting bit stream is 64 kbps. This system has been demonstrated to provide video of sufficient quality to allow remote driving of a High-Mobility Multipurpose Wheeled Vehicle at speeds up to 15 mph (24.1 kph) on a moguled dirt track. The nominal driving configuration provides a frame rate of 4 Hz, a compression per frame of 125:1, and a resulting latency of ~1s. This paper reviews the system approach and implementation, and further describes some of our experiences when using the system to support remote driving

Deterministic Surface Registration at 10Hz Based on Landmark Graphs With Prediction

Landmark graphs provide a means for surface registration, based on determining subgraph isomorphism to find scene-to-scene correspondences. Surface data used herein included both range and colour imagery. Images were acquired of a static scene from a moving sensor. The continuous motion allowed the sensor position to be predicted, which helped stabilize graph formation. Landmarks were determined using the KLT corner detector. Graph structure was established using nodes (landmarks) and edges that agreed well with predicted locations. Subgraph matching was approximated using the LeRP algorithm. A 6 DOF rigid transformation including translation and rotation was found via Horn’s method. Test results on real and synthetic images indicate that a substantial speed improvement is possible, with greater determinism than ICP, while maintaining accuracy. Tests incorporated relatively large image displacements, spanning up to 30% of the sensor FOV for the image stream. Mean absolute errors remained under 0.8% FOV. Mean compute rates were ≈ 10 Hz with standard deviation ranging 6-9%, for an image size of 200x200. Tests were run on a 900 MHz PC. 141 test trials are reported, with comparisons against a fast version of ICP

Structural Graph Matching With Polynomial Bounds On Memory and On Worst-Case Effort

A new method of structural graph matching is introduced and compared against an existing method and against the maximum common subgraph. The method is approximate with polynomial bounds on both memory and on the worst-case compute effort. Methods work on arbitrary types of graphs and tests with strongly regular graphs are included. No node or edge colors are needed in the methods; the common subgraph is extracted based in structural comparisons only. Monte Carlo trials are benchmarked with 100% additional (clutter) nodes. Results are shown to be typically within 1-2 nodes of the maximum common subgraph. Over 7500 test trials are reported with graphs up to 100 nodes

SIPTool: The \u27Signal and Image Processing Tool\u27 An Engaging Learning Environment

The ‘Signal and Image Processing Tool’ is a multimedia software environment for demonstrating and developing Signal & Image Processing techniques. It has been used at Cal Poly for three years. A key feature is extensibility via C/C++ programming. The tool has a minimal learning curve, making it amenable for weekly student projects. The software distribution includes multimedia demonstrations ready for classroom or laboratory use. SIPTool programming assignments strengthen the skills needed for life-long learning by requiring students to translate mathematical expressions into a standard programming language, to create an integrated processing system (as opposed to simply using canned processing routines)

NetExam: A Web-Based Assessment Tool for ABET2000

Abstract ⎯ NetExam is a web-based testing engine. In addition to automated testing and grading capabilities, NetExam computes statistics that are tied directly to program outcomes, for ABET2000 assessment purposes. NetExam provides advantages over scantron-style testing as it also presents statistics on program outcomes on the web. This facilitates review and black board-style comments by program constituents. Also, all of the exam generation, grading, statistics and program assessment features are integrated into the web-based system. First usage is planned for the 2001-2002 academic year

Fast Landmark-Based Registration via Deterministic and Efficient Processing, Some Preliminary Results

Preliminary results of a new method for range view registration are presented. The method incorporates the LeRP Algorithm, which is a deterministic means to approximate subgraph isomorphisms. Graphs are formed that describe salient scene features. Graph matching then provides the scene-to-scene correspondence necessary for registration. A graphical representation is invariant with respect to sensor standoff. Test results from real and synthetic images indicate that a reasonable tradeoff between speed and accuracy is achievable. A mean rotational error of ~1 degree was found for a variety of test cases. Mean compute times were found to be better than 2 Hz, with image sizes varying from 128x200 to 240x320. These tests were run on a 900 MHz PC. The greatest challenge to this approach is the stable localization and invariant characterization of image features via fast, deterministic techniques

Real-Time Range Image Segmentation Using Adaptive Kernels and Kalman Filtering

Segmentation is a fundamental process affecting the overall quality and utility of a machine vision system. Range Profile Tracking (RPT) is a systematic approach for stable, accurate and high speed segmentation of range images that is based on Kalman filtering. Tests of RPT have produced stable decompositions of second order surfaces bounded by jump and crease discontinuities, having a volumetric error of a few percent, in under 6 sec. for a wide variety of conditions. Results from over 900 tests on synthetic scenes and 150 real range images are presented