@conference {12570,
	title = {An ontology based approach for activity recognition from video},
	booktitle = {Proceedings of the 16th ACM international conference on Multimedia},
	series = {MM {\textquoteright}08},
	year = {2008},
	month = {2008///},
	pages = {709 - 712},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Representation and recognition of human activities is an important problem for video surveillance and security applications. Considering the wide variety of settings in which surveillance systems are being deployed, it is necessary to create a common knowledge-base or ontology of human activities. Most current attempts at ontology design in computer vision for human activities have been empirical in nature. In this paper, we present a more systematic approach to address the problem of designing ontologies for visual activity recognition. We draw on general ontology design principles and adapt them to the specific domain of human activity ontologies. Then, we discuss qualitative evaluation principles and provide several examples from existing ontologies and how they can be improved upon. Finally, we demonstrate quantitatively in terms of recognition performance, the efficacy and validity of our approach for bank and airport tarmac surveillance domains.},
	keywords = {activity ontologies, visual surveillance},
	isbn = {978-1-60558-303-7},
	doi = {10.1145/1459359.1459466},
	url = {http://doi.acm.org/10.1145/1459359.1459466},
	author = {Akdemir,Umut and Turaga,Pavan and Chellapa, Rama}
}
@conference {13173,
	title = {Top-down, bottom-up multivalued default reasoning for identity maintenance},
	booktitle = {Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks},
	series = {VSSN {\textquoteright}06},
	year = {2006},
	month = {2006///},
	pages = {79 - 86},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Persistent tracking systems require the capacity to track individuals by maintaining identity across visibility gaps caused by occlusion events. In traditional computer vision systems, the flow of information is typically bottom-up. The low level image processing modules take video input, perform early vision tasks such as background subtraction and object detection,and pass this information to the high level reasoning module. This paper describes the architecture of a system that uses top-down information flow to perform identity maintenance across occlusion events. This system uses the high level reasoning module to provide control feedback to the low level image processing module to perform forensic analysis of archival video and actively acquire information required to arrive at identity decisions. This functionality is in addition to traditional bottom-up reasoning about identity, employing contextual cues and appearance matching, within the multivalued default logic framework proposed in [18]. This framework, in addition to bestowing upon the system the property of nonmonotonicity, also allows for it to qualitatively encode its confidence in the identity decisions it takes.},
	keywords = {default logic, identity maintenance, nonmonotonic reasoning, tracking, visual surveillance},
	isbn = {1-59593-496-0},
	doi = {10.1145/1178782.1178795},
	url = {http://doi.acm.org/10.1145/1178782.1178795},
	author = {Shet,Vinay D. and Harwood,David and Davis, Larry S.}
}
