title: Combine tracking and detection
body: <p>I'm currently working on a multiple object tracking problem. I think using Tracking-by-Detection is a good choice. However, I do not know how to combine tracking and detection result so that detection can help improve tracking results.</p>
  
  <p>I'm using Faster-RCNN, tensorflow object detection API as a simple starting point for detection. 
  For tracking, I use KCF algorithm from opencv. </p>
  
  <p>Detection is unstable because every frame is independent to the model, while tracking is much more stable.</p>
  
  <p>Although tracking is more stable, when the object moves, tracker can not follow the object, which is not accurate.</p>
  
  <p>So I'm thinking of combining these two methods to improve my result as both stable and accurate.</p>
  
  <p>I have a background of computer vision but I'm new to this field (Multiple Object Tracking). Could anyone please give me some advice on how I should deal with this kind of problem ?</p>
  
  <p>Thanks alot! :)</p>