Repository landing page

We are not able to resolve this OAI Identifier to the repository landing page. If you are the repository manager for this record, please head to the Dashboard and adjust the settings.

Novel Architecture for Human Re-Identification with a Two-Stream Neural Network and Attention Mechanism

Abstract

This paper proposes a novel architecture that utilises an attention mechanism in conjunction with multi-stream convolutional neural networks (CNN) to obtain high accuracy in human re-identification (Reid). The proposed architecture consists of four blocks. First, the pre-processing block prepares the input data and feeds it into a spatial-temporal two-stream CNN (STC) with two fusion points that extract the spatial-temporal features. Next, the spatial-temporal attentional LSTM block (STA) automatically fine-tunes the extracted features and assigns weight to the more critical frames in the video sequence by using an attention mechanism. Extensive experiments on four of the most popular datasets support our architecture. Finally, the results are compared with the state of the art, which shows the superiority of this approach

Similar works

Full text

thumbnail-image

Computing and Informatics (E-Journal - Institute of Informatics, SAS, Bratislava)

redirect
Last time updated on 28/11/2022

Having an issue?

Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.