Automated camera layout to satisfy task-specific and floor plan-specific coverage requirements
01 Sep 2006-Computer Vision and Image Understanding (Elsevier Science Inc.)-Vol. 103, Iss: 3, pp 156-169
TL;DR: The general camera placement problem is first defined with assumptions that are more consistent with the capabilities of real world cameras, and a solution to this problem is obtained via binary optimization over a discrete problem space.
About: This article is published in Computer Vision and Image Understanding.The article was published on 2006-09-01. It has received 229 citations till now. The article focuses on the topics: Smart camera & Floor plan.
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TL;DR: This paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies which are adaptive, distributed, asynchronous, and verifiably correct.
Abstract: This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.
2,198 citations
TL;DR: A broad survey of developments in active vision in robotic applications over the last 15 years is provided, e.g. object recognition and modeling, site reconstruction and inspection, surveillance, tracking and search, as well as robotic manipulation and assembly, localization and mapping, navigation and exploration.
Abstract: In this paper we provide a broad survey of developments in active vision in robotic applications over the last 15 years. With increasing demand for robotic automation, research in this area has received much attention. Among the many factors that can be attributed to a high-performance robotic system, the planned sensing or acquisition of perceptions on the operating environment is a crucial component. The aim of sensor planning is to determine the pose and settings of vision sensors for undertaking a vision-based task that usually requires obtaining multiple views of the object to be manipulated. Planning for robot vision is a complex problem for an active system due to its sensing uncertainty and environmental uncertainty. This paper describes such problems arising from many applications, e.g. object recognition and modeling, site reconstruction and inspection, surveillance, tracking and search, as well as robotic manipulation and assembly, localization and mapping, navigation and exploration. A bundle of solutions and methods have been proposed to solve these problems in the past. They are summarized in this review while enabling readers to easily refer solution methods for practical applications. Representative contributions, their evaluations, analyses, and future research trends are also addressed in an abstract level.
398 citations
Cites methods from "Automated camera layout to satisfy ..."
...A solution to this problem is obtained via binary optimization over a discrete problem space (Erdem and Sclaroff 2006)....
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TL;DR: A comprehensive survey of geometric and topological coverage models for camera networks from the literature is presented and the properties of a hypothetical inclusively general model of each type are derived.
Abstract: Modeling the coverage of a sensor network is an important step in a number of design and optimization techniques. The nature of vision sensors presents unique challenges in deriving such models for camera networks. A comprehensive survey of geometric and topological coverage models for camera networks from the literature is presented. The models are analyzed and compared in the context of their intended applications, and from this treatment the properties of a hypothetical inclusively general model of each type are derived.
149 citations
Cites background or methods from "Automated camera layout to satisfy ..."
...Erdem and Sclaroff (2006), Bodor et al. (2007), Malik and Bajcsy (2008), Yao et al. (2008), and Mittal and Davis (2008) all use distance along the optical axis as the single parameter for the resolution constraint....
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...One of the experiments of Erdem and Sclaroff (2006) specifies a higher resolution requirement on certain parts of the floor plan....
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...Erdem and Sclaroff (2006) and Wang et al. (2009) also use the relevance volume as the allowable viewpoint position set....
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...Erdem and Sclaroff (2006) and Hörster and Lienhart (2009) do not appear to share this lineage, and explicitly cite the complexity of their respective optimization methods as motivating their restriction to two dimensions....
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...This turns out to be a satisfactory definition in two dimensions; Erdem and Sclaroff (2006) and Hörster and Lienhart (2009) arrive at the same by way of the pinhole camera model, perhaps elucidating how its value should be determined from a given camera system....
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References
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01 Jan 1972
TL;DR: The principles of integer programming are directed toward finding solutions to problems from the fields of economic planning, engineering design, and combinatorial optimization as mentioned in this paper, which is a standard of graduate-level courses since 1972.
Abstract: The principles of integer programming are directed toward finding solutions to problems from the fields of economic planning, engineering design, and combinatorial optimization. This highly respected and much-cited text, a standard of graduate-level courses since 1972, presents a comprehensive treatment of the first two decades of research on integer programming.
4,336 citations
07 Aug 2002
TL;DR: In this paper, the authors describe decentralized control laws for the coordination of multiple vehicles performing spatially distributed tasks, which are based on a gradient descent scheme applied to a class of decentralized utility functions that encode optimal coverage and sensing policies.
Abstract: This paper describes decentralized control laws for the coordination of multiple vehicles performing spatially distributed tasks. The control laws are based on a gradient descent scheme applied to a class of decentralized utility functions that encode optimal coverage and sensing policies. These utility functions are studied in geographical optimization problems and they arise naturally in vector quantization and in sensor allocation tasks. The approach exploits the computational geometry of spatial structures such as Voronoi diagrams.
2,445 citations
Posted Content•
TL;DR: This paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies which are adaptive, distributed, asynchronous, and verifiably correct.
Abstract: This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.
2,198 citations
"Automated camera layout to satisfy ..." refers background in this paper
...The rule of thumb is: no matter how good and efficient a vision algorithm might be, it will perform miserably if poor decisions are made in the up-front task of choosing the cameras, setting their parameters, and designing their layout in the region of interest....
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Book•
01 Jan 1987TL;DR: In this paper, the authors proposed a visibility algorithm based on three-dimensions and miscellany of the polygons, and showed that minimal guard covers threedimensions of the polygon.
Abstract: Polygon partitions Orthogonal polygons Mobile guards Miscellaneous shapes Holes Exterior visibility Visibility groups Visibility algorithms Minimal guard covers Three-dimensions and miscellany.
1,547 citations
"Automated camera layout to satisfy ..." refers background in this paper
...One of the key questions raised by a camera network is where to position the individual cameras given certain constraints....
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