Research Article
Reproducibility of AOD Algorithm: An Experimental evaluation for Key-Predictors Identification
@ARTICLE{10.4108/eai.13-7-2018.164099, author={Monika Monika and Kamaldeep Kaur}, title={Reproducibility of AOD Algorithm: An Experimental evaluation for Key-Predictors Identification}, journal={EAI Endorsed Transactions on Context-aware Systems and Applications}, volume={7}, number={20}, publisher={EAI}, journal_a={CASA}, year={2020}, month={4}, keywords={Abandoned Object Detection, AOD Algorithm, Benchmark Dataset, Reproducibility, Video Processing}, doi={10.4108/eai.13-7-2018.164099} }- Monika Monika
Kamaldeep Kaur
Year: 2020
Reproducibility of AOD Algorithm: An Experimental evaluation for Key-Predictors Identification
CASA
EAI
DOI: 10.4108/eai.13-7-2018.164099
Abstract
INTRODUCTION: Today surveillance systems are widespread across the globe for monitoring of various activities. Abandoned Object Detection (AOD) and identifying its location is one of them. In this paper, we evaluated the reproducibility of an existing AOD algorithm on benchmark video datasets.
OBJECTIVES: The purpose of the study is to identify the key predictors for developing a generalized AOD algorithm.
METHODS: The algorithm selection is performed by a detailed exploration of repositories through various research questions (RQs).
RESULTS: After the study video summarization, Correct Detection Rate (CDR), generalized Region of Interest (ROI), background learning, and interaction factor considered for enhancing the AOD algorithm.
CONCLUSION: Identification of suspiciousness has various measures depending upon perception, on the basis of results explored the existing algorithm can be improved using key-predictors with observational parameters.
Copyright © 2020 Monika et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
