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Hello! I am working on an application where I need to detect and track people in a crowded indoor area(like a mall). Right now I am using the OpenCV Background Subtraction class(MOG2) to detect blobs and a Kalman filter and Hungarian Algorithm for tracking(based on this video https://www.youtube.com/watch?v=2fW5TmAtAXM). The issues I'm having are i) the blobs merging together when two people come close to each other ii) Parts of the person not getting detected which leads to false and multiple detections on a person iii) The background subtraction itself leading to too many false detections. I would like to know your suggestions to improve this and any solutions to fix the problems? Thanks in advance!

Hello! I am working on an application where I need to detect and track people in a crowded indoor area(like a mall). Right now I am using the OpenCV Background Subtraction class(MOG2) to detect blobs and a Kalman filter and Hungarian Algorithm for tracking(based on this video https://www.youtube.com/watch?v=2fW5TmAtAXM). The issues I'm having are i) the blobs merging together when two people come close to each other ii) Parts of the person not getting detected which leads to false and multiple detections on a person iii) The background subtraction itself leading to too many false detections. I would like to know your suggestions to improve this and any solutions to fix the problems? Thanks in advance!

Hello! I am working on an application where I need to detect and track people in a crowded indoor area(like a mall). Right now I am using the OpenCV Background Subtraction class(MOG2) to detect blobs and a Kalman filter and Hungarian Algorithm for tracking(based on this video https://www.youtube.com/watch?v=2fW5TmAtAXM). The issues I'm having are i) the blobs merging together when two people come close to each other ii) Parts of the person not getting detected which leads to false and multiple detections on a person iii) The background subtraction itself leading to too many false detections. I would like to know your suggestions to improve this and any solutions to fix the problems? Thanks in advance!advance! BTW, I'm using OpenCV 3.1,C++

Hello! I am working on an application where I need to detect and track people in a crowded indoor area(like a mall). Right now I am using the OpenCV Background Subtraction class(MOG2) to detect blobs and a Kalman filter and Hungarian Algorithm for tracking(based on this video https://www.youtube.com/watch?v=2fW5TmAtAXM).