On the Hardware/Software Design and Implementation of a High Definition Multiview Video Surveillance System

published_or_final_versio

Long Range Automated Persistent Surveillance

This dissertation addresses long range automated persistent surveillance with focus on three topics: sensor planning, size preserving tracking, and high magnification imaging. field of view should be reserved so that camera handoff can be executed successfully before the object of interest becomes unidentifiable or untraceable. We design a sensor planning algorithm that not only maximizes coverage but also ensures uniform and sufficient overlapped camera’s field of view for an optimal handoff success rate. This algorithm works for environments with multiple dynamic targets using different types of cameras. Significantly improved handoff success rates are illustrated via experiments using floor plans of various scales. Size preserving tracking automatically adjusts the camera’s zoom for a consistent view of the object of interest. Target scale estimation is carried out based on the paraperspective projection model which compensates for the center offset and considers system latency and tracking errors. A computationally efficient foreground segmentation strategy, 3D affine shapes, is proposed. The 3D affine shapes feature direct and real-time implementation and improved flexibility in accommodating the target’s 3D motion, including off-plane rotations. The effectiveness of the scale estimation and foreground segmentation algorithms is validated via both offline and real-time tracking of pedestrians at various resolution levels. Face image quality assessment and enhancement compensate for the performance degradations in face recognition rates caused by high system magnifications and long observation distances. A class of adaptive sharpness measures is proposed to evaluate and predict this degradation. A wavelet based enhancement algorithm with automated frame selection is developed and proves efficient by a considerably elevated face recognition rate for severely blurred long range face images

Experiences with the JPL telerobot testbed: Issues and insights

The Jet Propulsion Laboratory's (JPL) Telerobot Testbed is an integrated robotic testbed used to develop, implement, and evaluate the performance of advanced concepts in autonomous, tele-autonomous, and tele-operated control of robotic manipulators. Using the Telerobot Testbed, researchers demonstrated several of the capabilities and technological advances in the control and integration of robotic systems which have been under development at JPL for several years. In particular, the Telerobot Testbed was recently employed to perform a near completely automated, end-to-end, satellite grapple and repair sequence. The task of integrating existing as well as new concepts in robot control into the Telerobot Testbed has been a very difficult and timely one. Now that researchers have completed the first major milestone (i.e., the end-to-end demonstration) it is important to reflect back upon experiences and to collect the knowledge that has been gained so that improvements can be made to the existing system. It is also believed that the experiences are of value to the others in the robotics community. Therefore, the primary objective here will be to use the Telerobot Testbed as a case study to identify real problems and technological gaps which exist in the areas of robotics and in particular systems integration. Such problems have surely hindered the development of what could be reasonably called an intelligent robot. In addition to identifying such problems, researchers briefly discuss what approaches have been taken to resolve them or, in several cases, to circumvent them until better approaches can be developed

Earth orbital teleoperator system man-machine interface evaluation

The teleoperator system man-machine interface evaluation develops and implements a program to determine human performance requirements in teleoperator systems

MARS Science Laboratory Post-Landing Location Estimation Using Post2 Trajectory Simulation

The Mars Science Laboratory (MSL) Curiosity rover landed safely on Mars August 5th, 2012 at 10:32 PDT, Earth Received Time. Immediately following touchdown confirmation, best estimates of position were calculated to assist in determining official MSL locations during entry, descent and landing (EDL). Additionally, estimated balance mass impact locations were provided and used to assess how predicted locations compared to actual locations. For MSL, the Program to Optimize Simulated Trajectories II (POST2) was the primary trajectory simulation tool used to predict and assess EDL performance from cruise stage separation through rover touchdown and descent stage impact. This POST2 simulation was used during MSL operations for EDL trajectory analyses in support of maneuver decisions and imaging MSL during EDL. This paper presents the simulation methodology used and results of pre/post-landing MSL location estimates and associated imagery from Mars Reconnaissance Orbiter s (MRO) High Resolution Imaging Science Experiment (HiRISE) camera. To generate these estimates, the MSL POST2 simulation nominal and Monte Carlo data, flight telemetry from onboard navigation, relay orbiter positions from MRO and Mars Odyssey and HiRISE generated digital elevation models (DEM) were utilized. A comparison of predicted rover and balance mass location estimations against actual locations are also presented