A Survey on use of Ontology for Complex Human Activity Recognition in Video Sequences

Video Surveillance systems are ubiquitous in today’s world. Traditional Video SurveillanceSystems are being replaced by intelligent systems and this process has been happening rapidlysince decades. This work lists the Activity Recognition approaches to recognize complex humanactivities. Knowledge based approaches with video sensors are brought out to be the vitalapproach in comparison with the data-based approaches, because data driven models have totrain on huge data. We investigate the significance of both the approaches in handling complexactivities with a long sequence of primitive activities. Knowledge driven approaches withOntology models the domain expertise to support the long sequenced activity recognition.Hence, the approaches supported by the Ontology for handling complex activities are found tobe the most suited model for the recognition of complex human activities