<p>Take a look of the work done by Rodrigo Benenson.</p>

<p><a href="https://arxiv.org/abs/1602.01237" rel="nofollow noreferrer">How Far are We from Solving Pedestrian Detection?</a></p>

<p><a href="http://rodrigob.github.io/documents/2014_eccvw_ten_years_of_pedestrian_detection_with_supplementary_material.pdf" rel="nofollow noreferrer">Ten Years of pedestrian detection</a></p>

<p>It's a really good starting point for pedestrian detection and understand what are the different approaches that has been used in the last decade.</p>
Roboust Human detection and tracking in a crowded area
<p>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 <a href="https://www.youtube.com/watch?v=2fW5TmAtAXM" rel="nofollow noreferrer">this video</a>).</p>

<p>The issues I'm having are: </p>

<ol>
<li>The blobs merging together when two people come close to each other </li>
<li>Parts of the person not getting detected which leads to false and multiple detections on a person </li>
<li>The background subtraction itself results in too many false detections.</li>
</ol>

<p>I would like to know your suggestions to improve this and any solutions to fix these problems? Is there an alternate way to detect humans?I am not using HOG because I didn't get detections unless the entire body of the person was in the frame, and it resulted in false detections as well.</p>

<p>Thanks in advance!</p>

<p>BTW, I'm using OpenCV 3.1,C++</p>

<p>edit:</p>

<p>This what I mean by false detections with HOG:</p>

<p><a href="https://i.stack.imgur.com/UQlnw.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/UQlnw.png" alt="enter image description here"></a></p>

<p><a href="https://i.stack.imgur.com/9pYpx.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/9pYpx.png" alt="Person not detected when only half is body is present in the frame"></a></p>

<p><a href="https://i.stack.imgur.com/DDkMp.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/DDkMp.png" alt="enter image description here"></a></p>