Filters








113,921 Hits in 2.8 sec

Mixture models for optical flow computation [chapter]

Allan Jepson, Michael Black
1995 DIMACS Series in Discrete Mathematics and Theoretical Computer Science  
We use a simple extension of the EM-algorithm to compute a maximum likelihood estimate for the various motion parameters.  ...  Preliminary experiments indicate that this approach is computationally e cient and can provide robust estimates of the optical ow v alues in the presence of outliers and multiple motions.  ...  Heel for providing the Pepsi-can image sequence and J. Bergen for providing the transparency sequence.  ... 
doi:10.1090/dimacs/019/14 dblp:conf/dimacs/JepsonB93 fatcat:4vw5ixgwnnfi5cii7wc7d3j72u

Mixture models for optical flow computation

A. Jepson, M.J. Black
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition  
We use a simple extension of the EM-algorithm to compute a maximum likelihood estimate for the various motion parameters.  ...  Preliminary experiments indicate that this approach is computationally e cient and can provide robust estimates of the optical ow v alues in the presence of outliers and multiple motions.  ...  Heel for providing the Pepsi-can image sequence and J. Bergen for providing the transparency sequence.  ... 
doi:10.1109/cvpr.1993.341161 dblp:conf/cvpr/JepsonB93 fatcat:puoadjzdnffatfncfkeeagr3hm

Real-Time Detection and Tracking of Moving Object

Jianguo Tao, Changhong Yu
2008 2008 Second International Symposium on Intelligent Information Technology Application  
It will prove very helpful for public safety.  ...  Based on above discussion in my research work I have decided to develop intelligent framework for Real time motion detection or recognition for appropriate thing or object.  ...  Here foreground used for optical flow is foreground extracted using Gaussian Mixture Modelling techniques.  ... 
doi:10.1109/iita.2008.428 fatcat:nb23cmneqjctjhvhvdtobo54q4

HUMAN ACTIVITY DETECTION AND ACTION RECOGNITION IN VIDEOS USING CONVOLUTIONAL NEURAL NETWORKS

Jagadeesh Basavaiah, Chandrashekar Mohan Patil
2020 Journal of Information and Communication Technology  
Human activity recognition from video scenes has become a significant area of research in the field of computer vision applications. Action recognition is one of the most challenging  ...  This research received no specific grant from any funding agency in the public, commercial, or not-for profit sectors.  ...  Center, Department of Electronics and Communication Engineering, Vidyavardhaka College of Engineering, Mysuru, India which is recognized by the Visvesvaraya Technological University, Belagavi, India for  ... 
doi:10.32890/jict2020.19.2.1 fatcat:cafcrtepljesvnidrwfjuo2foa

An Efficient Algorithm for Real Time Moving Object Detection using GMM and Optical Flow
English

Parth Kishorbhai Bathia, Hetal Vala,
2015 International Journal of Innovative Research in Computer and Communication Engineering  
Here for proposed work used Gaussian Mixture Model and Optical Flow technique for the moving object detection.  ...  Gaussian Mixture Model is better extract the foreground object but it more time consuming and Optical Flow is faster for moving object detection but it is not more accurate so by using these two approaches  ...  In fig 6 it is detect motion using Gaussian Mixture Model and Optical Flow which is our proposed method. V.  ... 
doi:10.15680/ijircce.2015.0306021 fatcat:j56cjpnvffbprkn4jveymswhbu

Scene understanding by statistical modeling of motion patterns

Imran Saleemi, Lance Hartung, Mubarak Shah
2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition  
We propose a mixture model representation of salient patterns of optical flow, and present an algorithm for learning these patterns from dense optical flow in a hierarchical, unsupervised fashion.  ...  Using low level cues of noisy optical flow, K-means is employed to initialize a Gaussian mixture model for temporally segmented clips of video.  ...  Process flow of our approach: Grouping of frames into video clips, optical flow computation, Gaussian mixture model learning by K-means, filtering of noisy Gaussian components, inter-component spatiotemporal  ... 
doi:10.1109/cvpr.2010.5539884 dblp:conf/cvpr/SaleemiHS10 fatcat:jfjregphlrck7f2rcwklyrhjcm

Robust foreground segmentation using improved Gaussian Mixture Model and optical flow

Hajer Fradi, Jean-Luc Dugelay
2012 2012 International Conference on Informatics, Electronics & Vision (ICIEV)  
In this context, Gaussian Mixture Model (GMM) background subtraction has been widely employed.  ...  However, the background model estimation step is still problematic; the main difficulty is to decide which distributions of the mixture belong to the background.  ...  It is obtained by computing the optical flow between consecutives frames, then a measure for uniformity of motion is applied. For optical flow computation, several algorithms exist in the literature.  ... 
doi:10.1109/iciev.2012.6317376 fatcat:aarehtcxezhy7lbwxdtuidunpy

Sensory Anticipation of Optical Flow in Mobile Robotics [article]

Arturo Ribes, Jesús Cerquides, Yiannis Demiris, Ramón López de Mántaras
2012 arXiv   pre-print
The learnt model is used to anticipate the optical flow up to a given time horizon and to predict an imminent collision by using reinforcement learning.  ...  A sensorimotor model is acquired online by the mobile robot using a state-of-the-art method that learns the optical flow distribution in images, both in space and time.  ...  First, the active mixture components are computed from the current optical flow values for each position in the sample grid.  ... 
arXiv:1210.1104v1 fatcat:gl35755p4jc6dpzf6vpxeonxlm

Incremental learning of an optical flow model for sensorimotor anticipation in a mobile robot

Arturo Ribes, Jesus Cerquides, Yiannis Demiris, Ramon Lopez de Mantaras
2012 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL)  
The learnt model is used to anticipate the optical flow up to a given time horizon and to predict an imminent collision by using reinforcement learning.  ...  A sensorimotor model is acquired online by the mobile robot using a state-of-the-art method that learns the optical flow distribution in images, both in space and time.  ...  First, the active mixture components are computed from the current optical flow values for each position in the sample grid.  ... 
doi:10.1109/devlrn.2012.6400589 dblp:conf/icdl-epirob/RibesCDM12 fatcat:zknqdafpabccrak6f4t6npzywa

Histogram-based foreground object extraction for indoor and outdoor scenes

Mandar Kulkarni
2010 Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing - ICVGIP '10  
In our approach the spatial histogram of a single background image is modeled as Mixture of Gaussians and this model is updated after every few frames.  ...  To mitigate the errors caused due to movement of the background objects (e.g tree leaves in outdoor scenes), we also incorporate optical flow in an efficient manner.  ...  Estimating optical flow on complete images is often computationally expensive.  ... 
doi:10.1145/1924559.1924579 dblp:conf/icvgip/Kulkarni10 fatcat:3fsthxz5b5a47i224ltyjntryu

Vehicle Detection, Tracking and Counting Using Gaussian Mixture Model and Optical Flow

Muhammad Moin Akhtar, Yong Li, Lei Zhong, Ayesha Ansari
2020 Journal of Engineering Research and Reports  
The proposed approach consists of an optical flow method with a Gaussian mixture model (GMM) to obtain an absolute shape of particular moving objects which improves the detection performance of moving  ...  PROPOSED METHOD The proposed method is based on the Gaussian mixture model (GMM) and optical flow.  ...  Gaussian Mixture Model (GMM) Gaussian mixture model consists of a mixture of K Gaussian distribution illustrated by these parameters: mean (µ), weight (w), and variance (σ2).  ... 
doi:10.9734/jerr/2020/v15i217141 fatcat:iyu3u2kpqjf4phia7vgfj63ov4

Spatiotemporal Background Subtraction Using Minimum Spanning Tree and Optical Flow [chapter]

Mingliang Chen, Qingxiong Yang, Qing Li, Gang Wang, Ming-Hsuan Yang
2014 Lecture Notes in Computer Science  
modeling and subtraction is a fundamental research topic in computer vision.  ...  Additionally, optical flow estimation can be used to track the foreground pixels and integrated with a temporal M -smoother to ensure temporally-consistent background subtraction.  ...  The computational cost of proposed spatiotemporally-consistent background model is much higher due to the use of optical flow which is known to be slow.  ... 
doi:10.1007/978-3-319-10584-0_34 fatcat:kfa3ovgtubczvmxumy5wihshcq

Anomaly detection in crowded scenes

Vijay Mahadevan, Weixin Li, Viral Bhalodia, Nuno Vasconcelos
2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition  
The model for normal crowd behavior is based on mixtures of dynamic textures and outliers under this model are labeled as anomalies.  ...  Three properties are identified as important for the design of a localized video representation suitable for anomaly detection in such scenes: 1) joint modeling of appearance and dynamics of the scene,  ...  of PCA models of optic flow.  ... 
doi:10.1109/cvpr.2010.5539872 dblp:conf/cvpr/MahadevanLBV10 fatcat:gm55i2kv4rbehpvujfqajhrxoi

Analysis of Persistent Motion Patterns Using the 3D Structure Tensor

John Wright, Robert Pless
2005 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1  
In scenes with multiple global motion patterns, a mixture model (of these global distributions) automatically factors background motion into a set of flow fields corresponding to the different motions.  ...  Capturing statistics of the spatiotemporal derivatives at each pixel can efficiently model surprisingly complicated motion patterns.  ...  The covariance matrix permits deeper analysis than just computing an estimate of the optic flow at each pixel. One simple confidence measure for the optic flow estimate is S = 1 − λ 3 /λ 2 .  ... 
doi:10.1109/acvmot.2005.21 dblp:conf/wacv/WrightP05 fatcat:pcjyxsjlibbu7lsqtkwv6fnp3y

Modeling of flow and heat transfer in a vertical reactor for the MOCVD of zirconium-based coatings [chapter]

M. Dauelsberg, L. Kadinski, C. Schmidt, C. Allenbach, M. Morstein
1998 Simulation of Semiconductor Processes and Devices 1998  
Flow and heat transfer in a vertical reactor used for the MOCVD growth of zirconium based compounds is studied by computational modeling.  ...  The verification of computational predictions is done by temperature measurements. Flow regimes are compared with respect to the flow structure and temperature distribution in the reactor.  ...  Modeling approach The modeling approach consists of computing the laminar, hyposonic (low Mach number) non-isothermal flow for a gas mixture with high temperature and density gradients.  ... 
doi:10.1007/978-3-7091-6827-1_7 fatcat:fkabvcyb3vhnffbcsaygxpohya
« Previous Showing results 1 — 15 out of 113,921 results