A review on human action analysis in videos for retrieval applications

Ramezani, Mohsen

doi:10.1007/s10462-016-9473-y

Cited by 50 publications

(16 citation statements)

References 82 publications

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“…Recognition of human behavior within vehicles are becoming increasingly important due to the successful mapping of driver and passenger activities [7] in autonomous vehicle. With the accurate classification about what the driver is doing, the human machine interaction can be directed to the suitable modalities.…”

Section: Autonomous Driving Vehiclementioning

confidence: 99%

Study on Machine Learning and Deep Learning Methods for Human Action Recognition

Rajendran¹,

Lee²,

Gopi³

et al. 2020

Preprint

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With the evolution of computing technology in many application like human robot interaction, human computer interaction and health-care system, 3D human body models and their dynamic motions has gained popularity. Human performance accompanies human body shapes and their relative motions. Research on human activity recognition is structured around how the complex movement of a human body is identified and analyzed. Vision based action recognition from video is such kind of tasks where actions are inferred by observing the complete set of action sequence performed by human. Many techniques have been revised over the recent decades in order to develop a robust as well as effective framework for action recognition. In this survey, we summarize recent advances in human action recognition, namely the machine learning approach, deep learning approach and evaluation of these approaches.

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Section: Autonomous Driving Vehiclementioning

confidence: 99%

Study on Machine Learning and Deep Learning Methods for Human Action Recognition

Rajendran¹,

Lee²,

Gopi³

et al. 2020

Preprint

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“…In recent times, due to thriving growth of technology, people can with ease upload and share videos on the Internet. However, administrating and retrieving videos according to the video content from a query is becoming a great challenge as most of the search engines use the associated text data to manage video data [7]. The text data, such as titles, tags, descriptions and keywords, can be obscure, incorrect and irrelevant making the video retrieval unsuccessful.…”

Section: A Video Retrievalmentioning

confidence: 99%

“…For example, in [8], researchers in a bid to help children with autism created a video retrieval framework by computing the similarity between action representations and implemented framework in a classroom setting to retrieve videos of children suffering from autism. Compared to conventional Human Action Recognition task, the video retrieval task relies more on the retrieval ranking instead of classification [7].…”

Section: A Video Retrievalmentioning

confidence: 99%

A Survey on Human Action Recognition

Volvoikar¹

2019

IJRASET

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In Computer Vision and image processing field, understanding the actions of human from videos is demanding task. Humans performing the actions in the video is automatically cognized and designating their actions is the prime purpose of astute video systems. Its motive is to acknowledge the actions and objectives of one or more multiple objects from a series of examination on the action of objects and their environmental condition. Human action recognition has gained popularity because of its wide applicability varying from Content-based Video Analytics, Visual Surveillance and Video Indexing etc. This paper depicts survey on person to person interaction, single person and multiple people action recognition and deciphers the methodologies and limitations of diverse methods for human action recognition are explored.

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“…Object representation is a method to describe an object, through which objects can be easily detected and retrieved from video stream. In general, objects can be represented by their shapes such that points based method, primitive geometric shapes and silhouette and contour and by their appearances such as probability density and templates [28]. The disadvantage of object features is that objects recognition in the video is complicated therefore; present algorithms focus on identifying a specific part of object like faces, rather than the whole object.…”

Section: Object Featuresmentioning

confidence: 99%

Semantic Based Video Retrieval System: Survey

Abdulmunem

Hato

2018

ijs

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In this review paper a number of studies and researches are surveyed, in order to assist the upcoming researchers, to know about the techniques available in the field of semantic based video retrieval. The video retrieval system is used for finding the users' desired video among a huge number of available videos on the Internet or database. This paper gives a general discussion on the overall process of the semantic video retrieval phases. In addition to its present a generic review of techniques that has been proposed to solve the semantic gap as the major scientific problem in semantic based video retrieval. The semantic gap is formed because of the difference between the low level features that are extracted from video content and user's perceptions of these features in a real world. The transformation of low level features of the video content into meaningful semantic concepts is a research topic that has received considerable attention in recent years.

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A review on human action analysis in videos for retrieval applications

Cited by 50 publications

References 82 publications

Study on Machine Learning and Deep Learning Methods for Human Action Recognition

Study on Machine Learning and Deep Learning Methods for Human Action Recognition

A Survey on Human Action Recognition

Semantic Based Video Retrieval System: Survey

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