Masterqsx

Improve Background Subtraction with Aggregated Saliency

Contributor: Shengxin Qian | Mentor: Antonella Cascitelli

1. Overview

This project contains the implementation of three saliency algorithms:

• DeepGaze1 [1] Image based saliency
  • This is a supervised learning algorithm based on the linear combination of AlexNet 5th convolution layers.
  • This algorithm takes advantage of the high level features generated by those pretrained Deep Neural Network.
  • The training of this algorithm is slow but it is fast when estimating saliency.
• This algorithm can achieve 0.84 AUC on MIT Saliency Benchmark which is one of the best score.