Modeling camera coverage is essential in many visual sensor applications. Particularly in visual surveillance, planning the coverage modeling is critical to estimate the coverage and to design the sensor deployment. Given the environment representation, the coverage model produces the sensor coverage based on the device specifications; however, analyzing the visibility in an arbitrary scene is a challenging part. This letter proposes a preliminary setup based on imaging techniques to assist in solving the camera placement problem. The proposed setup computes the camera coverage in a two-dimensional digitized floor-plan. Additionally, a pixelwise line drawing routine analyzes the ray's visibility from the viewpoint to the width of the field of view. Three commercial surveillance cameras are modeled and the obtained result forms the necessary coverage table for subsequent optimization tasks. Finally, the placement based on the proposed modeling setup is carried out and the result is evaluated against benchmark coverage modeling methods.

Optimizing the visual sensors coverage to perform security monitoring tasks has an undeniable impact on the performance as well as the cost of video surveillance systems. The placement arrangement is an NP-hard problem, in which the main target is to seek an approximate solution. This paper addresses the placement of security cameras to maximize the total coverage of the camera network. The coverage of the visual sensor array is modeled descriptively using an enhanced pinhole camera model to obtain the layout of the field of view. The main contribution of the paper is to introduce a dynamic programming algorithm, which defines an optimal policy for solving the visual sensor coverage problem. To validate the proposed algorithm, we compared the outcomes of the dynamic programming algorithm with the existing benchmarking placement optimization techniques. The assessment reveals the effectiveness of the proposed dynamic programming solution to maximize the coverage for a set of predefined locations.

Modern surveillance systems rely on coverage overlapping to attain multi-viewing capabilities and to support coverage redundancy. This paper examines the coverage overlapping configurations in visual surveillance systems. The paper proposes a robust dynamic programming framework to optimize visual surveillance sensor coverage overlaps. Based on visual sensor parameters information, and the features of the area to be monitored, the paper uses a deterministic modeling approach to model the sensor coverage in a two-dimensional space. Then, the minimization and the maximization arrangements of the coverage overlapping is formulated as discrete optimization problems. The obtained solutions from the dynamic programming technique are evaluated with respect to local and global greedy search algorithms. The results reveal the feasibility of the proposed technique compared to the benchmarked optimization methods in terms of the amount of coverage redundancy.

Indoor positioning has gained popularity recently due to its potential to be used in the increasing complexity of indoor environment. Unfortunately GPS signals are restricted to outdoor purposes. The main objective of this work is to design a new method to develop indoor positioning navigation system without using wireless technology through image processing. Apart from that, the work also aims to develop an interactive indoor navigation system. Augmented reality is being used to superimpose the directional signage on the real view of the indoor environment in 3D form. Along with the 3D guides, voice guidance will be output from the system to assist users in identifying their locations easily. Overall, the scope of study involves research on augmented reality, audio API, and other additional techniques that can improve the program in computing the route. The idea of this work can be broadly applied to mobile devices such as mobile phones and PDA as an added indoor navigation functionality without the use of GPS and wireless communication. The proposed system has been tested at the ground floor of the Information Resource Centre (IRC) in Universiti Teknologi PETRONAS and the results show the flexibility of the system in navigating 12 locations and ability to handle up to 30 possible routes.