1,521 research outputs found
Attentive monitoring of multiple video streams driven by a Bayesian foraging strategy
In this paper we shall consider the problem of deploying attention to subsets
of the video streams for collating the most relevant data and information of
interest related to a given task. We formalize this monitoring problem as a
foraging problem. We propose a probabilistic framework to model observer's
attentive behavior as the behavior of a forager. The forager, moment to moment,
focuses its attention on the most informative stream/camera, detects
interesting objects or activities, or switches to a more profitable stream. The
approach proposed here is suitable to be exploited for multi-stream video
summarization. Meanwhile, it can serve as a preliminary step for more
sophisticated video surveillance, e.g. activity and behavior analysis.
Experimental results achieved on the UCR Videoweb Activities Dataset, a
publicly available dataset, are presented to illustrate the utility of the
proposed technique.Comment: Accepted to IEEE Transactions on Image Processin
Fast-Forward Video Based on Semantic Extraction
Thanks to the low operational cost and large storage capacity of smartphones
and wearable devices, people are recording many hours of daily activities,
sport actions and home videos. These videos, also known as egocentric videos,
are generally long-running streams with unedited content, which make them
boring and visually unpalatable, bringing up the challenge to make egocentric
videos more appealing. In this work we propose a novel methodology to compose
the new fast-forward video by selecting frames based on semantic information
extracted from images. The experiments show that our approach outperforms the
state-of-the-art as far as semantic information is concerned and that it is
also able to produce videos that are more pleasant to be watched.Comment: Accepted for publication and presented in 2016 IEEE International
Conference on Image Processing (ICIP
Enhancing camera surveillance using computer vision: a research note
- The growth of police operated surveillance cameras has
out-paced the ability of humans to monitor them effectively. Computer vision is
a possible solution. An ongoing research project on the application of computer
vision within a municipal police department is described. The paper aims to
discuss these issues.
- Following the demystification of
computer vision technology, its potential for police agencies is developed
within a focus on computer vision as a solution for two common surveillance
camera tasks (live monitoring of multiple surveillance cameras and summarizing
archived video files). Three unaddressed research questions (can specialized
computer vision applications for law enforcement be developed at this time, how
will computer vision be utilized within existing public safety camera
monitoring rooms, and what are the system-wide impacts of a computer vision
capability on local criminal justice systems) are considered.
- Despite computer vision becoming accessible to law
enforcement agencies the impact of computer vision has not been discussed or
adequately researched. There is little knowledge of computer vision or its
potential in the field.
- This paper introduces and discusses computer
vision from a law enforcement perspective and will be valuable to police
personnel tasked with monitoring large camera networks and considering computer
vision as a system upgrade
- …