3-D Model-Based Multi-Camera Deployment: A Recursive Convex Optimization Approach

Zhang, Xuebo; Chen, Xiang; Alarcon-Herrera, Jose Luis

doi:10.1109/tmech.2015.2411593

Cited by 45 publications

(40 citation statements)

References 27 publications

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“…Several works expand the two-dimensional world view of the AGP into a more realistic three-dimensional case [ 7 , 16 , 20 , 23 , 24 , 25 , 26 , 27 , 28 ]. However, while many of these models can be simplified when you care about a planar scene, these models require extra computation to be used for occlusion checking which is unnecessary when dealing with a planar scene.…”

Section: Related Workmentioning

confidence: 99%

Optimal Camera Pose and Placement Configuration for Maximum Field-of-View Video Stitching

Watras

Kim

Liu

et al. 2018

Sensors

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An optimal camera placement problem is investigated. The objective is to maximize the area of the field of view (FoV) of a stitched video obtained by stitching video streams from an array of cameras. The positions and poses of these cameras are restricted to a given set of selections. The camera array is designed to be placed inside the abdomen to support minimally invasive laparoscopic surgery. Hence, a few non-traditional requirements/constraints are imposed: Adjacent views are required to overlap to support image registration for seamless video stitching. The resulting effective FoV should be a contiguous region without any holes and should be a convex polygon. With these requirements, traditional camera placement algorithms cannot be directly applied to solve this problem. In this work, we show the complexity of this problem grows exponentially as a function of the problem size, and then present a greedy polynomial time heuristic solution that approximates well to the globally optimal solution. We present a new approach to directly evaluate the combined coverage area (area of FoV) as the union of a set of quadrilaterals. We also propose a graph-based approach to ensure the stitching requirement (overlap between adjacent views) is satisfied. We present a method to find a convex polygon with maximum area from a given polygon. Several design examples show that the proposed algorithm can achieve larger FoV area while using much less computing time.

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Section: Related Workmentioning

confidence: 99%

Optimal Camera Pose and Placement Configuration for Maximum Field-of-View Video Stitching

Watras

Kim

Liu

et al. 2018

Sensors

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“…Contrary to our case, in this work the environment to cover is assumed to be initially known. [39] proposed an alternative approach, based on recursive convex optimization, for multi-camera deployment to visually cover a three-dimensional object, which is still considered perfectly known from the beginning.…”

Section: Static Coveragementioning

confidence: 99%

A Common Optimization Framework for Multi-Robot Exploration and Coverage in 3D Environments

Renzaglia

Dibangoye

Doze

et al. 2020

J Intell Robot Syst

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This paper studies the problems of static coverage and autonomous exploration of unknown three-dimensional environments with a team of cooperating aerial vehicles. Although these tasks are usually considered separately in the literature, we propose a common framework where both problems are formulated as the maximization of online acquired information via the definition of single-robot optimization functions, which differs only slightly in the two cases to take into account the static and dynamic nature of coverage and exploration respectively. A common derivative-free approach based on a stochastic approximation of these functions and their successive optimization is proposed, resulting in a fast and decentralized solution. The locality of this methodology limits however this solution to have local optimality guarantees and specific additional layers are proposed for the two problems to improve the final performance. Specifically, a Voronoi-based initialization step is added for the coverage problem and a combination with a frontier-based approach is proposed for the exploration case. The resulting algorithms are finally tested in simulations and compared with possible alternatives.

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“…Besides, for more precise monitoring tasks, there is resolution requirement to recognize a real object in camera sensor networks. Based on a convex optimization approach, a method of multi-camera deployment for visual coverage of a 3D object surface was proposed in [ 40 ]. The authors proposed a new resolution criterion, which simultaneously considered both the distance and the view angle.…”

Section: Related Workmentioning

confidence: 99%

Barrier Coverage for 3D Camera Sensor Networks

Zhang

et al. 2017

Sensors

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Barrier coverage, an important research area with respect to camera sensor networks, consists of a number of camera sensors to detect intruders that pass through the barrier area. Existing works on barrier coverage such as local face-view barrier coverage and full-view barrier coverage typically assume that each intruder is considered as a point. However, the crucial feature (e.g., size) of the intruder should be taken into account in the real-world applications. In this paper, we propose a realistic resolution criterion based on a three-dimensional (3D) sensing model of a camera sensor for capturing the intruder’s face. Based on the new resolution criterion, we study the barrier coverage of a feasible deployment strategy in camera sensor networks. Performance results demonstrate that our barrier coverage with more practical considerations is capable of providing a desirable surveillance level. Moreover, compared with local face-view barrier coverage and full-view barrier coverage, our barrier coverage is more reasonable and closer to reality. To the best of our knowledge, our work is the first to propose barrier coverage for 3D camera sensor networks.

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3-D Model-Based Multi-Camera Deployment: A Recursive Convex Optimization Approach

Cited by 45 publications

References 27 publications

Optimal Camera Pose and Placement Configuration for Maximum Field-of-View Video Stitching

Optimal Camera Pose and Placement Configuration for Maximum Field-of-View Video Stitching

A Common Optimization Framework for Multi-Robot Exploration and Coverage in 3D Environments

Barrier Coverage for 3D Camera Sensor Networks

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