Tracking People by Detection Using CNN Features

Citations of this article
Mendeley users who have this article in their library.


Multiple people tracking is an important task for surveillance. Recently, tracking by detection methods had emerged as immediate effect of deep learning remarkable achievements in object detection. In this paper, we use Faster-RCNN for detection and compare two methods for object association. The first method is simple Euclidean distance and the second is more complicated Siamese neural network. The experiment result show that simple Euclidean distance gives promising result as object association method, but it depends heavily on the robustness of detection process on individual frames.




Chahyati, D., Fanany, M. I., & Arymurthy, A. M. (2017). Tracking People by Detection Using CNN Features. In Procedia Computer Science (Vol. 124, pp. 167–172). Elsevier B.V.

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free