Real-time tracking of multiple objects in space-variant vision based on magnocellular visual pathway

As a basic aspect of computer vision, reliable tracking of multiple objects is still an open and challenging issue for both theory studies and real applications. A novel multi-object tracking algorithm based on multiple cameras is proposed in this paper. We obtain the foreground likelihood maps in each view by modeling the background using the codebook algorithm. The view-to-view homographies are computed using several landmarks on the chosen plane. Then, we achieve the location information of multi-target at chest layer and realize the tracking task. The proposed algorithm does not require detecting the vanishing points of cameras, which reduces the complexity and improves the accuracy of the algorithm. The experimental results show that our method is robust to the occlusion and could satisfy the real-time tracking requirement.

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Real-Time Tracking of Single and Multiple Objects from Depth-Colour Imagery Using 3D Signed Distance Functions

International Journal of Computer Vision ◽

10.1007/s11263-016-0978-2 ◽

2017 ◽

Vol 124 (1) ◽

pp. 80-95 ◽

Cited By ~ 11

Author(s):

C. Y. Ren ◽

V. A. Prisacariu ◽

O. Kähler ◽

I. D. Reid ◽

D. W. Murray

Keyword(s):

Real Time ◽

Distance Functions ◽

Multiple Objects ◽

Signed Distance ◽

Real Time Tracking ◽

Signed Distance Functions

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Real-time tracking of multiple objects using adaptive correlation filters with complex constraints

Optics Communications ◽

10.1016/j.optcom.2013.07.044 ◽

2013 ◽

Vol 309 ◽

pp. 265-278 ◽

Cited By ~ 26

Author(s):

Victor H. Diaz-Ramirez ◽

Viridiana Contreras ◽

Vitaly Kober ◽

Kenia Picos

Keyword(s):

Real Time ◽

Correlation Filters ◽

Multiple Objects ◽

Complex Constraints ◽

Real Time Tracking

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A Robust Algorithm for Real Time Tracking With Optical Flow

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.a4419.119119 ◽

2019 ◽

Vol 9 (1) ◽

pp. 887-892

Keyword(s):

Optical Flow ◽

Object Tracking ◽

Real Time ◽

Traffic Monitoring ◽

Moving Object ◽

Computational Time ◽

Multiple Objects ◽

Flow Information ◽

Data Processor ◽

Real Time Tracking

Object tracking is a troublesome undertaking and significant extent in data processor perception and image handling community. Some of the applications are protection surveillance, traffic monitoring on roads, offense detection and medical imaging. In this paper a recent technique for tracking of moving object is intended. Optical flow information authorizes us to know the displacement and speed of objects personate in a scene. Apply optical flow to the image gives flow vectors of the points to distinguishing the moving aspects. Optical flow is accomplished by Lucas canade algorithm. This algorithm is superior to other algorithms. The outcomes reveals that the intend algorithm is efficient and accurate object tracking method. This paper depicts a smoothing algorithm to track the moving object of both single and multiple objects in real time. The main issue of high computational time is greatly reduced in this proposed work

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