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Shafiq Ahmad is PhD Research Fellow at Pattern Analysis & Computer Vision (PAVIS) research group at Italian Institute of Technology (iit). Shafiq does research in Computer Vision and Deep Learning.
The large-scale use of surveillance cameras in public spaces raised severe concerns about an individual privacy breach. Introducing privacy and security in video surveillance systems, primarily in person re-identification (re-id), is quite challenging. Event cameras are novel sensors, which only respond to brightness changes in the scene. This char...
In this article, we propose two kinds of improvements to a baseline tracker that employs the tracking-by-detection framework. First, we explore different feature spaces by employing features commonly used in object detection to improve the performance of detector in feature space. Second, we propose a robust scale estimation algorithm that estimate...
1) I find corner (Harris Corner) on 1st frame. then
2) Compute Optical Flow and find moition vector (Ux,Vy) between two frames, at corners.
3)then update Coordinates of Corners by adding Ux and Vy. (Cx+Ux, Cy+Vy).
But it fail to track corners. If any one have KLT Simple Tracker Matlab code kindly share with me.
In the Attached Paper, I have a problem in Mean Shift Vector Equation 10.
Does M(X) => Mean Shift Vector are contain both Vx and Vy or single value ?
I have only problem in how to calculate Target Model & Target Candidates Kernel density from histograms (for gray scale images.)
Let suppose we have histograms H1 and H2 of Target Model & Target Candidates respectively. I want to compute Gaussian kernel Density.
Suppose, We have Optical Flow [u v]=[6 6] (only for one Pixel) between two frames (frame1 and frame2).
I want to remove [u' , v']=[4 , 4] motion from frame2 so that when I measure Optical Flow again betw Frame1 and Frame2, motion is [2 , 2].
First, we explore different feature spaces for object detection to improve the performance of detector in feature space. Second, we propose a robust scale estimation algorithm that estimates the accurate size of the object in the current frame.