Coverage Optimization of Camera Network for Continuous Deformable Object

TL;DR

This paper presents a method for deploying cameras to continuously monitor deformable objects by selecting key feature points and optimizing camera placement using an improved wolf pack algorithm, demonstrated through simulations.

Contribution

It introduces a novel approach combining feature point selection and an improved wolf pack algorithm for efficient camera deployment on deformable objects.

Findings

Effective coverage of deformable objects demonstrated in simulations

Reduced computational complexity through feature point selection

Improved optimization algorithm enhances deployment efficiency

Abstract

In this paper, a deformable object is considered for cameras deployment with the aim of visual coverage. The object contour is discretized into sampled points as meshes, and the deformation is represented as continuous trajectories for the sampled points. To reduce the computational complexity, some feature points are carefully selected representing the continuous deformation process, and the visual coverage for the deformable object is transferred to cover the specific feature points. In particular, the vertexes of a rectangle that can contain the entire deformation trajectory of every sampled point on the object contour are chosen as the feature points. An improved wolf pack algorithm is then proposed to solve the optimization problem. Finally, simulation results are given to demonstrate the effectiveness of the proposed deployment method of camera network.