Logo Recognition with an Incremental Learning method and Consensus for enabling Blockchain Implementations

EasyChair Preprint no. 925

Abstract

A large amount of non-processed visual information is uploaded in social networks every day. Different features can be analyzed from the images such as objects, scenes, sentiments, people’s mood, color, etc. In this paper, we propose a novel method to detect, locate and classify logos in images, based on consensus. First, we present a basic logo recognition method. Second, an incremental learning algorithm is proposed to detect logos of any class by just using a synthetic image template, without the need of annotating a training set. Then, a crowdsourced solution (collaborative network) is generated within a VisualAD platform to carry out the consensus between several executions of the incremental learning method. The predictions will be the result of individual predictions from several users that improve the recognition. Finally, the principles enabling its Blockchain implementation are set and considerations on their extension to visual identity

Keyphrases: Blockchain, Collaborative Network, consensus, Distributed Ledger Technology, Logo Recognition

@Booklet{EasyChair:925,
  author = {Josep Lluis De La Rosa and Andres El-Fakdi and Fabio Bacchini and Xesca Amengual Gaya},
  title = {Logo Recognition with an Incremental Learning method and Consensus for enabling Blockchain Implementations},
  howpublished = {EasyChair Preprint no. 925},
  doi = {10.29007/62b2},
  year = {EasyChair, 2019}}