Tools
Sorted by:
Try your query at:
 |
 |
 |
 |
 |
 |
Results 1 - 10
of
160
Traffic Video Segmentation Using Adaptive-K Gaussian Mixture Model
"... Abstract. Video segmentation is an important phase in video based traffic surveillance applications. The basic task of traffic video segmentation is to classify pixels in the current frame to road background or moving vehicles, and casting shadows should be taken into account if exists. In this pape ..."
Abstract
-
Cited by 11 (2 self)
- Add to MetaCart
. In this paper, a modified online EM procedure is proposed to construct Adaptive-K Gaussian Mixture Model (AKGMM) in which the dimension of the parameter space at each pixel can adaptively reflects the complexity of pattern at the pixel. A heuristic background components selection rule is developed to make pixel
Effective Gaussian Mixture Learning for Video Background Subtraction
- IEEE Transactions on pattern analysis and machine intelligence
"... Abstract—Adaptive Gaussian mixtures have been used for modeling nonstationary temporal distributions of pixels in video surveillance applications. However, a common problem for this approach is balancing between model convergence speed and stability. This paper proposes an effective scheme to improv ..."
Abstract
-
Cited by 134 (0 self)
- Add to MetaCart
Abstract—Adaptive Gaussian mixtures have been used for modeling nonstationary temporal distributions of pixels in video surveillance applications. However, a common problem for this approach is balancing between model convergence speed and stability. This paper proposes an effective scheme
Video Segmentation and Annotation Using Gaussian Mixtures
"... This paper describes a new approach to the segmentation and annotation prob-lem using Gaussian mixture model descriptors. These have several advantages over conventional, histogram-based techniques, including: a rigorous statistical basis; the possibility of encoding spatial, colour, texture and mot ..."
Abstract
- Add to MetaCart
This paper describes a new approach to the segmentation and annotation prob-lem using Gaussian mixture model descriptors. These have several advantages over conventional, histogram-based techniques, including: a rigorous statistical basis; the possibility of encoding spatial, colour, texture
Segmentation of Vehicles in Traffic Video
"... Abstract — Segmentation of moving objects in a scene is often desired in applications such as video surveillance, where our interest is in monitoring for example, cars and people. In the project, we look at traffic videos and investigate two approaches that can be used to segment vehicles from the b ..."
Abstract
- Add to MetaCart
Abstract — Segmentation of moving objects in a scene is often desired in applications such as video surveillance, where our interest is in monitoring for example, cars and people. In the project, we look at traffic videos and investigate two approaches that can be used to segment vehicles from
Adaptive Gaussian Mixture Model for Skin Color Segmentation
"... Abstract—Skin color based tracking techniques often assume a static skin color model obtained either from an offline set of library images or the first few frames of a video stream. These models can show a weak performance in presence of changing lighting or imaging conditions. We propose an adaptiv ..."
Abstract
-
Cited by 9 (0 self)
- Add to MetaCart
an adaptive skin color model based on the Gaussian mixture model to handle the changing conditions. Initial estimation of the number and weights of skin color clusters are obtained using a modified form of the general Expectation maximization algorithm, The model adapts to changes in imaging conditions
Models, Gaussian Mixture
"... Abstract — Motion trajectories provide rich spatio-temporal information about an object’s activity. Developing scalable activity recognition algorithms based on this high dimensionality cue is an extremely challenging task. This paper presents novel classification algorithms for recognizing object a ..."
Abstract
- Add to MetaCart
of change in curvature and the subtrajectories are represented by their Principal Component Analysis (PCA) coefficients. We first present a framework to robustly estimate the multivariate probability density function (PDF) based on PCA coefficients of the subtrajectories using Gaussian Mixture Models (GMM
On-Road Automotive Vehicle Detection using Gaussian Mixture Model and NNs
"... This work presents an approach in study for the vehicle traffic control through the use of computer vision techniques. The videos captured are processed frame-to-frame, where the movement of objects is segmented using the Gaussian Mixture Model. Later, characteristics are extracted and applied to a ..."
Abstract
- Add to MetaCart
This work presents an approach in study for the vehicle traffic control through the use of computer vision techniques. The videos captured are processed frame-to-frame, where the movement of objects is segmented using the Gaussian Mixture Model. Later, characteristics are extracted and applied to a
A Bayesian Framework for Gaussian Mixture Background Modeling
- In Proceedings. International Conference on Image Processing, 2003
"... Background subtraction is an essential processing component for many video applications. However, its development has largely been application driven and done in ad hoc manners. In this paper, we provide a Bayesian formulation of background segmentation based on Gaussian mixture models. We show that ..."
Abstract
-
Cited by 23 (0 self)
- Add to MetaCart
Background subtraction is an essential processing component for many video applications. However, its development has largely been application driven and done in ad hoc manners. In this paper, we provide a Bayesian formulation of background segmentation based on Gaussian mixture models. We show
Foreground Segmentation Using Adaptive Mixture Models in Color and Depth
- in IEEE Workshop on Detection and Recognition of Events in Video
, 2001
"... Segmentation of novel or dynamic objects in a scene, often referred to as "background subtraction" or "foreground segmentation", is a critical early in step in most computer vision applications in domains such as surveillance and human-computer interaction. All previously describ ..."
Abstract
-
Cited by 67 (2 self)
- Add to MetaCart
and software for real-time computation of depth imagery makes better approaches possible. We propose a method for modeling the background that uses per-pixel, time-adaptive, Gaussian mixtures in the combined input space of depth and luminance-invariant color. This combination in itself is novel, but we further
Discovery and Segmentation of Activities in Video
"... AbstractÐHidden Markov models (HMMs) have become the workhorses of the monitoring and event recognition literature because they bring to time-series analysis the utility of density estimation and the convenience of dynamic time warping. Once trained, the internals of these models are considered opaq ..."
Abstract
- Add to MetaCart
of scene activity, and detection of anomalous behavior. We demonstrate with models of office activity and outdoor traffic, showing how the framework learns principal modes of activity and patterns of activity change. We then show how this framework can be adapted to infer hidden state from extremely
Results 1 - 10
of
160
