Results 211 to 220 of about 456,062 (261)
Some of the next articles are maybe not open access.
A Fluid Background Traffic Model
2009 IEEE International Conference on Communications, 2009Background traffic has a significant impact on the behavior of network services and protocols. However, a detailed model of the background traffic can be extremely time consuming in simulation. In this paper, we extend our previous hybrid model that combines fluid and packet-oriented characterization of network traffic for a realistic representation of
Ting Li 0024, Jason Liu 0001
openaire +1 more source
Stochastic approximation for background modelling
Computer Vision and Image Understanding, 2011Many background modelling approaches are based on mixtures of multivariate Gaussians with diagonal covariance matrices. This often yields good results, but complex backgrounds are not adequately captured, and post-processing techniques are needed.
Ezequiel López-Rubio +1 more
openaire +1 more source
Scale-Corrected Background Modeling
2017 14th Conference on Computer and Robot Vision (CRV), 2017Modern security cameras are capable of capturing high-resolution HD or 4K videos and support embedded analytics capable of automatically tracking objects such as people and cars moving through the scene. However, due to a lack of computational power on these cameras, the embedded video analytics cannot utilize the full available video resolution ...
Parthipan Siva, Michael Jamieson
openaire +1 more source
Aggregated Dynamic Background Modeling
2006 International Conference on Image Processing, 2006Standard practices in background modeling learn a separate model for every pixel in the image. However, in dynamic scenes the connection between an observation and the place where it was observed is much less important and is usually random. For example, a wave observed in an ocean scene could easily have been observed at another place in the image ...
Amit Adam, Ehud Rivlin, Ilan Shimshoni
openaire +1 more source
2016
This chapter contextualizes the role of smart meters in smart grid initiatives around the world to show that the smart grid concept goes beyond energy supplier modernization. In addition, this chapter presents the security model and the privacy model for Privacy-Preserving Protocols (PPPs).
openaire +1 more source
This chapter contextualizes the role of smart meters in smart grid initiatives around the world to show that the smart grid concept goes beyond energy supplier modernization. In addition, this chapter presents the security model and the privacy model for Privacy-Preserving Protocols (PPPs).
openaire +1 more source
A Bayesian Approach to Background Modeling
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops, 2006Learning background statistics is an essential task for several visual surveillance applications such as incident detection and traf.c management. In this paper, we propose a new method for modeling background statistics of a dynamic scene. Each pixel is represented with layers of Gaussian distributions.
Oncel Tuzel +2 more
openaire +1 more source
Multiscale background modelling and segmentation
2009 16th International Conference on Digital Signal Processing, 2009A new multiscale approach to motion based segmentation of objects in video sequences is presented. While image features extracted at multiple scales are commonly used within the pattern recognition community, they have seldom been employed for background modelling and subtraction. The paper describes a methodology for maintaining an explicit background
Dubravko Culibrk +2 more
openaire +1 more source
Background of Modelling Approaches and Tools
2019This chapter illustrates the state of the art of the risk analysis methods and models for road tunnels with particular reference to the users’ egress models.
Borghetti F. +3 more
openaire +2 more sources
2013
Background models are often used in video surveillance systems to find moving objects in an image sequence from a static camera. These models are often built under the assumption that the foreground objects are not known in advance. This assumption has led us to model background using one-class SVM classifiers.
Assaf Glazer +2 more
openaire +1 more source
Background models are often used in video surveillance systems to find moving objects in an image sequence from a static camera. These models are often built under the assumption that the foreground objects are not known in advance. This assumption has led us to model background using one-class SVM classifiers.
Assaf Glazer +2 more
openaire +1 more source
Exemplar-based background model initialization
Proceedings of the third ACM international workshop on Video surveillance & sensor networks, 2005Most of the automated video-surveillance applications are based on background (BG) subtraction techniques, that aim at distinguishing moving objects in a static scene. These strategies strongly depend on the BG model, that has to be initialized and updated. A good initialization is crucial for the successive processing.
COLOMBARI, ANDREA +3 more
openaire +4 more sources