Deep Uncertainty Interpretation in Dyadic Human Activity Prediction

Ziaeefard, Maryam; Bergevin, Robert; Lalonde, Jean‐François

doi:10.1109/icmla.2017.00-55

Cited by 2 publications

(3 citation statements)

References 6 publications

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“… The temporal evaluation should improve the performance of [9].  When the activity is performed in a highly different way, errors may occur in [10].  The accuracy of [11] is same as the conventional methods accuracy.…”

Section: Discussionmentioning

confidence: 99%

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A survey on human activity prediction techniques

Manju¹,

Radha²

2018

IJATEE

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Nowadays, in order to prevent criminal behaviors or traffic accidents, video surveillance systems have become more and more popular in both outdoor and indoor places such as offices, departmental stores, public places, railway stations, and airports, etc. So, there is a great demand for an intelligent system to detect abnormal events in videos. In the surveillance tasks, people are generally the main objects of interest. Even though, recognition of human action is an emerging topic in the field of computer vision, detection of abnormal event is recently attracting more research attention. Abnormal behaviors can be identified as irregular behavior from the normal ones. Certainly, various techniques and approaches are proposed in order to ensure human safety. This paper presents a survey on different human activity prediction techniques in video surveillance system. Initially, different techniques developed by previous researchers are studied in detail. Then, the limitations in those techniques are also addressed to suggest further improvement on human activity prediction in videos using advanced techniques. The efficiency of the different human activity prediction techniques is proved by comparing their parameters. The comparison results show the best human activity prediction technique among them.

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Section: Discussionmentioning

confidence: 99%

“…A Deep learning framework [10] was proposed to analysis uncertainty related to dyadic human activities at a small temporal granularity. This framework reported at what degree of certainty each activity was occurred from definitely not occurring to definitely occurring.…”

Section: Survey On Prediction Of Human Activity In Videomentioning

confidence: 99%

A survey on human activity prediction techniques

Manju¹,

Radha²

2018

IJATEE

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“…On this subject, different research approaches have been used. For example, as a first approach, human behavior prediction models have been developed, either when decision-making is affected by peer pressure or by the inference of human activities based on short videos [ 151 ]. The approach ranges from psychological perspectives to assessing decision-making abstraction in human beings, both in regular contexts [ 152 ] or with imperfect information [ 153 ].…”

Section: Computational Methods For Decision-making Under Uncertaintymentioning

confidence: 99%

Decision-Making under Uncertainty for the Deployment of Future Hyperconnected Networks: A Survey

Alzate-Mejía

Santos-Boada

Amazonas

2021

Sensors

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Among the several emerging dimensioning, control and deployment of future communication network paradigms stands out the human-centric characteristic that creates an intricate relationship between telematics and human activities. The hard to model dynamics of user behavior introduces new uncertainties into these systems that give rise to difficult network resource management challenges. According to this context, this work reviews several decision-making computational methods under the influence of uncertainties. This work, by means of a systematic literature review, focuses on sensor-based Internet of Things scenarios such as Smart Spaces and Industry 4.0. According to our conclusions, it is mandatory to establish a means for modeling the human behavior context in order to improve resource assignment and management.

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Deep Uncertainty Interpretation in Dyadic Human Activity Prediction

Cited by 2 publications

References 6 publications

A survey on human activity prediction techniques

A survey on human activity prediction techniques

Decision-Making under Uncertainty for the Deployment of Future Hyperconnected Networks: A Survey

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