Recent rapid improvement in quality and resolution of imaging sensors and availability of low-cost smart cameras, together with the development of sensor network technology, have paved the way for creation of large scale camera networks.
Large scale camera trap grids were utilized in Guatemala and Peru to evaluate the impact of reduced-impact logging in certified concessions upon the large and medium-sized mammal fauna with special emphasis on jaguars (Panthera onca).
In this paper, a novel consensus-based adaptive algorithm for distributed target tracking in large scale camera networks is presented, aimed at situations characterized by limited sensing range, high-level clutter, and possibly occulted targets.
(This week, he will set up two large-scale cameras in the de Young tower and invite the public inside one on Tuesday and Wednesday, as crowds allow).
However, it is unfeasible to scale up to large-scale camera networks due to a mass of manually labeled efforts.
Moreover, it is feasible to achieve self-organized and scalable large-scale camera networks due to no need of human labeling efforts.
We use our framework to control and actuate a large-scale camera network so as to maximize the number and type of captured events.
As a result, compared to the supervised learning-based CLM, which needs a lot of human labeling efforts, especially with the increased size of datasets or number of camera pairs, the unsupervised learning-based CLM is more feasible to achieve self-organized and scalable large-scale camera networks.
Few works have been published on large scale source camera identification particularly on distributed computing such as [4, 6].
Manufacturers began to produce digital cameras on a large scale and at decreasing prices [119].
The high number of camera views and the quality of the camera views are unique for a large scale Naturalistic driving study.
