Dense and Sparse Optic Flows Aggregation for Accurate Motion Segmentation in Monocular Video Sequences

2012 ◽  
pp. 208-215
Author(s):  
Mihai Fǎgǎdar-Cosma ◽  
Vladimir-Ioan Creţu ◽  
Mihai Victor Micea
Keyword(s):  
Motion Segmentation ◽  
Video Sequences ◽  
Monocular Video ◽  
Optic Flows

Variable structure multiple model for articulated human motion tracking from monocular video sequences

2012 ◽  
Vol 55 (5) ◽  
pp. 1138-1150 ◽  
Author(s):  
Hong Han ◽  
MingLei Tong ◽  
ZhiChao Chen ◽  
YouJian Fan
Keyword(s):  
Motion Tracking ◽  
Variable Structure ◽  
Human Motion ◽  
Video Sequences ◽  
Multiple Model ◽  
Human Motion Tracking ◽  
Monocular Video ◽  
Articulated Human Motion

scholarly journals Motion Segmentation by New Three-View Constraint from a Moving Camera

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Fuyuan Xu ◽  
Guohua Gu ◽  
Kan Ren ◽  
Weixian Qian
Keyword(s):  
Motion Segmentation ◽  
Image Sequence ◽  
New Method ◽  
Video Sequences ◽  
Reference Plane ◽  
Projective Structure ◽  
Multiple Views ◽  
Epipolar Constraint ◽  
Surface Degradation ◽  
Moving Camera

We propose a new method for the motion segmentation using a moving camera. The proposed method classifies each image pixel in the image sequence as the background or the motion regions by applying a novel three-view constraint called the “parallax-based multiplanar constraint.” This new three-view constraint, being the main contribution of this paper, is derived from the relative projective structure of two points in three different views and implemented within the “Plane + Parallax” framework. The parallax-based multiplanar constraint overcomes the problem of the previous geometry constraint and does not require the reference plane to be constant across multiple views. Unlike the epipolar constraint, the parallax-based multiplanar constraint modifies the surface degradation to the line degradation to detect the motion objects followed by a moving camera in the same direction. We evaluate the proposed method with several video sequences to demonstrate the effectiveness and robustness of the parallax-based multiplanar constraint.

Modified Object Tracking and Counting Method Based on Gaussian Mixture Model

2013 ◽  
Vol 373-375 ◽  
pp. 598-602 ◽  
Author(s):  
Ming Jie Zhang ◽  
Bao Sheng Kang
Keyword(s):  
Object Tracking ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture ◽  
Video Sequences ◽  
Counting Method ◽  
Centroid Distance ◽  
Monocular Video ◽  
Video Scene ◽  
Detection Ratio

In a monocular video scene, in order to improve the efficiency of object tracking and counting under occlusion conditions. The article presents a scheme to automatically track and count people in a surveillance system. First, a modified Gaussian mixture model was employed to determine pedestrian objects from a static scene. To identify foreground objects by positions and sizes of foreground regions which were obtained. Moreover, the performance to track objects was improved by using the modified overlap tracker, the modified overlap tracker was used to analyze the centroid distance between neighboring objects and help object tracking and people counting in occlusion states of merging and splitting. On the experiments of tracking and counting people in three video sequences, the results show that the proposed method can improve the averaged detection ratio about 10% as compared to the conventional work.

Estimating heading direction from monocular video sequences using biologically-based sensors

2016 ◽  
Author(s):  
Michael J. Cree ◽  
John A. Perrone ◽  
Gehan Anthonys ◽  
Aden C. Garnett ◽  
Henry Gouk
Keyword(s):  
Video Sequences ◽  
Heading Direction ◽  
Monocular Video

A multiresolution spatiotemporal motion segmentation technique for video sequences based on pyramidal structures

2002 ◽  
Vol 23 (14) ◽  
pp. 1761-1769 ◽  
Author(s):  
J.A Rodrı́guez ◽  
C Urdiales ◽  
A Bandera ◽  
F Sandoval
Keyword(s):  
Motion Segmentation ◽  
Video Sequences ◽  
Segmentation Technique

Human pose modelling and body tracking from monocular video sequences

2007 ◽  
Author(s):  
Lim Siew Hod ◽  
G. Sainarayanan ◽  
Liau Chung Fan
Keyword(s):  
Video Sequences ◽  
Body Tracking ◽  
Monocular Video ◽  
Human Pose
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