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Sampling Based Sensor-Network Deployment
"... In this paper, we consider the problem of placing networked sensors in a way that guarantees coverage and connectivity. We focus on sampling based deployment and present algorithms that guarantee coverage and connectivity with a small number of sensors. We consider two different scenarios based on t ..."
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Cited by 40 (0 self)
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In this paper, we consider the problem of placing networked sensors in a way that guarantees coverage and connectivity. We focus on sampling based deployment and present algorithms that guarantee coverage and connectivity with a small number of sensors. We consider two different scenarios based on the flexibility of deployment. If deployment has to be accomplished in one step, like airborne deployment, then the main question becomes how many sensors are needed. If deployment can be implemented in multiple steps, then awareness of coverage and connectivity can be updated. For this case, we present incremental deployment algorithms which consider the current placement to adjust the sampling domain. The algorithms are simple, easy to implement, and require a small number of sensors. We believe the concepts and algorithms presented in this paper will provide a unifying framework for existing and future deployment algorithms which consider many practical issues not considered in the present work.
A general method for sensor planning in multi-sensor systems: Extension to random occlusion
, 2005
"... Abstract. Systems utilizing multiple sensors are required in many domains. In this paper, we specifically concern our-selves with applications where dynamic objects appear randomly and the system is employed to obtain some user-specified characteristics of such objects. For such systems, we deal wit ..."
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Cited by 33 (1 self)
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Abstract. Systems utilizing multiple sensors are required in many domains. In this paper, we specifically concern our-selves with applications where dynamic objects appear randomly and the system is employed to obtain some user-specified characteristics of such objects. For such systems, we deal with the tasks of determining measures for evaluating their performance and of determining good sensor configurations that would maximize such measures for better system performance. We introduce a constraint in sensor planning that has not been addressed earlier: visibility in the presence of random occluding objects. Two techniques are developed to analyze such visibility constraints: a probabilistic approach to determine “average ” visibility rates and a deterministic approach to address worst-case scenarios. Apart from this constraint, other important constraints to be considered include image resolution, field of view, capture orientation, and algorithmic constraints such as stereo matching and background appearance. Integration of such constraints is performed via the development of a probabilistic framework that allows one to reason about different occlusion events and integrates different multi-view capture and visibility constraints in a natural way. Integration of the thus obtained capture quality measure across the region of interest yields a measure for the effectiveness of a sensor configuration and maximization of such measure yields sensor configurations that are
Multi-camera positioning to optimize task observability
- In IEEE Conference on Advanced Video and Signal Based Surveillance
, 2005
"... The performance of computer vision systems for measurement, surveillance, reconstruction, gait recognition, and many other applications, depends heavily on the placement of cameras observing the scene. This work addresses the question of the optimal placement of cameras to maximize the performance o ..."
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Cited by 7 (1 self)
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The performance of computer vision systems for measurement, surveillance, reconstruction, gait recognition, and many other applications, depends heavily on the placement of cameras observing the scene. This work addresses the question of the optimal placement of cameras to maximize the performance of real-world vision systems in a variety of applications. Specifically, our goal is to optimize the aggregate observability of the tasks being performed by the subjects in an area. We develop a general analytical formulation of the observation problem, in terms of the statistics of the motion in the scene and the total resolution of the observed actions, that is applicable to many observation tasks and multi-camera systems. An optimization approach is used to find the internal and external (mounting position and orientation) camera parameters that optimize the observation criteria. We demonstrate the method for multi-camera systems in real-world monitoring applications, both indoor and outdoor. I.
Can you see me now? Sensor positioning for automated and persistent surveillance
- IEEE Transactions on Systems, Man, and Cybernetics—Part B
, 2010
"... Abstract—Most existing camera placement algorithms focus on coverage and/or visibility analysis, which ensures that the object of interest is visible in the camera’s field of view (FOV). However, visibility, which is a fundamental requirement of object tracking, is insufficient for automated persist ..."
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Cited by 6 (1 self)
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Abstract—Most existing camera placement algorithms focus on coverage and/or visibility analysis, which ensures that the object of interest is visible in the camera’s field of view (FOV). However, visibility, which is a fundamental requirement of object tracking, is insufficient for automated persistent surveillance. In such applications, a continuous consistently labeled trajectory of the same object should be maintained across different camera views. Therefore, a sufficient uniform overlap between the cameras’ FOVs should be secured so that camera handoff can successfully and automatically be executed before the object of interest becomes untraceable or unidentifiable. In this paper, we propose sensor-planning methods that improve existing algorithms by adding handoff rate analysis. Observation measures are designed for various types of cameras so that the proposed sensor-planning algorithm is general and applicable to scenarios with different types of cameras. The proposed sensor-planning algorithm preserves necessary uniform overlapped FOVs between adjacent cameras for an optimal balance between coverage and handoff success rate. In addition, special considerations such as resolution and frontal-view requirements are addressed using two approaches: 1) direct constraint and 2) adaptive weights. The resulting camera placement is compared with a reference algorithm published by Erdem and Sclaroff. Significantly improved handoff success rates and frontal-view percentages are illustrated via experiments using indoor and outdoor floor plans of various scales. Index Terms—Camera handoff, camera placement, coverage analysis, multi-camera surveillance, sensor placement. I.
Algorithms for Distributed and Mobile Sensing
, 2004
"... Sensing remote, complex and large environments is an important task that arises in diverse applications including planetary exploration, monitoring forest fires and the surveillance of large factories. Currently, automation of such sensing tasks in complex environments is achieved either by deployin ..."
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Cited by 2 (0 self)
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Sensing remote, complex and large environments is an important task that arises in diverse applications including planetary exploration, monitoring forest fires and the surveillance of large factories. Currently, automation of such sensing tasks in complex environments is achieved either by deploying many stationary sensors to the environment, or by mounting a sensor on a mobile device and using the device to sense the environment. The
A new upper bound for the vcdimension of visibility regions
- In Proceedings of the 27th Symposium on Computational Geometry, SoCG ’11
, 2011
"... In this paper we are proving the following fact. Let P be an arbi-trary simple polygon, and let S be an arbitrary set of 15 points inside P. Then there exists a subset T of S that is not “visually discernible”, that is, T 6 = vis(v)∩S holds for the visibility regions vis(v) of all points v in P. In ..."
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Cited by 1 (0 self)
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In this paper we are proving the following fact. Let P be an arbi-trary simple polygon, and let S be an arbitrary set of 15 points inside P. Then there exists a subset T of S that is not “visually discernible”, that is, T 6 = vis(v)∩S holds for the visibility regions vis(v) of all points v in P. In other words, the VC-dimension d of visibility regions in a simple polygon cannot exceed 14. Since Valtr [15] proved in 1998 that d ∈ [6, 23] holds, no progress has been made on this bound. By -net theorems our reduction immediately implies a smaller upper bound to the number of guards needed to cover P. 1
Sampling-Based Coverage . . . Structures
, 2012
"... Path planning is an essential capability for autonomous robots, and many applica-tions impose challenging constraints alongside the standard requirement of obsta-cle avoidance. Coverage planning is one such task, in which a single robot must sweep its end effector over the entirety of a known worksp ..."
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Path planning is an essential capability for autonomous robots, and many applica-tions impose challenging constraints alongside the standard requirement of obsta-cle avoidance. Coverage planning is one such task, in which a single robot must sweep its end effector over the entirety of a known workspace. For two-dimensional environments, optimal algorithms are documented and well-understood. For three-dimensional structures, however, few of the available heuristics succeed over occluded regions and low-clearance areas. This thesis makes several contributions to sampling-based coverage path planning, for use on complex three-dimensional structures. First, we introduce a new algorithm for planning feasible coverage paths. It is more computationally efficient in problems of complex geometry than the well-known dual sampling method, especially when high-quality solutions are desired. Second, we present an improvement procedure that iteratively shortens and smooths a feasible coverage path; robot configurations are adjusted without violating any coverage con-straints. Third, we propose a modular algorithm that allows the simple components
Sampling-Based Coverage Path Planning for Complex 3D Structures
, 2012
"... Path planning is an essential capability for autonomous robots, and many applica-tions impose challenging constraints alongside the standard requirement of obsta-cle avoidance. Coverage planning is one such task, in which a single robot must sweep its end effector over the entirety of a known worksp ..."
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Path planning is an essential capability for autonomous robots, and many applica-tions impose challenging constraints alongside the standard requirement of obsta-cle avoidance. Coverage planning is one such task, in which a single robot must sweep its end effector over the entirety of a known workspace. For two-dimensional environments, optimal algorithms are documented and well-understood. For three-dimensional structures, however, few of the available heuristics succeed over occluded regions and low-clearance areas. This thesis makes several contributions to sampling-based coverage path planning, for use on complex three-dimensional structures. First, we introduce a new algorithm for planning feasible coverage paths. It is more computationally efficient in problems of complex geometry than the well-known dual sampling method, especially when high-quality solutions are desired. Second, we present an improvement procedure that iteratively shortens and smooths a feasible coverage path; robot configurations are adjusted without violating any coverage con-straints. Third, we propose a modular algorithm that allows the simple components
A Taxonomy of Visual Surveillance Systems A Taxonomy of Visual Surveillance Systems
"... This report is a part of the research work which is conducted to develop a generalized model to design surveillance systems. A generalized taxonomy is developed which has organized the core features of surveillance systems at one place and can be used as an important tool for designing surveillance ..."
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This report is a part of the research work which is conducted to develop a generalized model to design surveillance systems. A generalized taxonomy is developed which has organized the core features of surveillance systems at one place and can be used as an important tool for designing surveillance systems. The designers can use this taxonomy to design surveillance systems with reduced effort, time and cost. A Taxonomy of Visual Surveillance Systems iii ABSTRACT The increased security risk in society and the availability of low cost sensors and processors has expedited the research in surveillance systems. Visual surveillance systems provide real time monitoring of the environment. Designing an optimized surveillance system for a given application is a challenging task. Moreover, the choice of components for a given surveillance application out of a wide spectrum of available products is not an easy job. In this report, we formulate a taxonomy to ease the design and classification of surveillance systems by combining their main features. The taxonomy is based on three main models: behavioral model, implementation model, and actuation model. The behavioral model helps to understand the behavior of a surveillance problem. The model is a set of functions such as detection, positioning, identification, tracking, and content handling. The behavioral model can be used to pinpoint the functions which are necessary for a particular situation. The implementation model structures the decisions which are necessary to implement the surveillance functions, recognized by the behavioral model. It is a set of constructs such as sensor type, node connectivity and node fixture. The actuation model is responsible for taking precautionary measures when a surveillance system detects some abnormal situation. A number of surveillance systems are investigated and analyzed on the basis of developed taxonomy. The taxonomy is general enough to handle a vast range of surveillance systems. It has organized the core features of surveillance systems at one place. It may be considered an important tool when designing surveillance systems. The designers can use this tool to design surveillance systems with reduced effort, cost, and time.
