A fast and self-adaptive on-line learning detection system

Mukesh Prasad, Ding Rong Zheng, Domingo Mery, Deepak Puthal, Suresh Sundaram, Chin Teng Lin

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations


This paper proposes a method to allow users to select target species for detection, generate an initial detection model by selecting a small piece of image sample and as the movie plays, continue training this detection model automatically. This method has noticeable detection results for several types of objects. The framework of this study is divided into two parts: the initial detection model and the online learning section. The detection model initialization phase use a sample size based on the proportion of users of the Haar-like features to generate a pool of features, which is used to train and select effective classifiers. Then, as the movie plays, the detecting model detects the new sample using the NN Classifier with positive and negative samples and the similarity model calculates new samples based on the fusion background model to calculate a new sample and detect the relative similarity to the target. From this relative similarity-based conservative classification of new samples, the conserved positive and negative samples classified by the video player are used for automatic online learning and training to continuously update the classifier. In this paper, the results of the test for different types of objects show the ability to detect the target by choosing a small number of samples and performing automatic online learning, effectively reducing the manpower needed to collect a large number of image samples and a large amount of time for training. The Experimental results also reveal good detection capability.

Original languageBritish English
Pages (from-to)13-22
Number of pages10
JournalProcedia Computer Science
StatePublished - 2018
Event3rd International Neural Network Society Conference on Big Data and Deep Learning, INNS BDDL 2018 - Sanur, Bali, Indonesia
Duration: 17 Apr 201819 Apr 2018


  • learning from video
  • Object detection
  • On-line learning
  • real-time streaming


Dive into the research topics of 'A fast and self-adaptive on-line learning detection system'. Together they form a unique fingerprint.

Cite this