scholarly journals Interaction Relational Network for Mutual Action Recognition

2021 ◽  
pp. 1-1
Author(s):  
Mauricio Perez ◽  
Jun Liu ◽  
Alex C. Kot
Keyword(s):  
Action Recognition ◽  
Relational Network ◽  
Mutual Action

Improving Action Recognition via Temporal and Complementary Learning

2021 ◽  
Vol 12 (3) ◽  
pp. 1-24
Author(s):  
Nour Eldin Elmadany ◽  
Yifeng He ◽  
Ling Guan
Keyword(s):  
Action Recognition ◽  
Network Performance ◽  
Recognition Performance ◽  
Information Modeling ◽  
Local Network ◽  
Temporal Representation ◽  
Learning Techniques ◽  
Temporal Learning ◽  
Relational Network

In this article, we study the problem of video-based action recognition. We improve the action recognition performance by finding an effective temporal and appearance representation. For capturing the temporal representation, we introduce two temporal learning techniques for improving long-term temporal information modeling, specifically Temporal Relational Network and Temporal Second-Order Pooling-based Network. Moreover, we harness the representation using complementary learning techniques, specifically Global-Local Network and Fuse-Inception Network. Performance evaluation on three datasets (UCF101, HMDB-51, and Mini-Kinetics-200) demonstrated the superiority of the proposed framework compared to the 2D Deep ConvNets-based state-of-the-art techniques.

The call to Hawaii: Holistic practitioners’ perspectives of their communicative practices of healing

2009 ◽  
Vol 5 (2) ◽  
pp. 133-144 ◽  
Author(s):  
Patricia Geist-Martin ◽  
Catherine Becker ◽  
Summer Carnett ◽  
Katherine Slauta
Keyword(s):  
Health Care ◽  
Healing Process ◽  
Holistic Health ◽  
Communicative Practices ◽  
Ethnographic Interviews ◽  
Health Care Practices ◽  
Wide Range ◽  
Care Practices ◽  
Holistic Health Care ◽  
Mutual Action

The big island of Hawaii has been named the healing island – a place with varied interpretations of healing, health, and a wide range of holistic health care practices. This research explores the perspectives of holistic providers about the communicative practices they believe are central to their interactions with patients. Intensive ethnographic interviews with 20 individuals revealed that they perceive their communication with clients as centered on four practices, specifically: (a) reciprocity – a mutual action or exchange in which both the practitioner and patient are equal partners in the healing process; (b) responsibility – the idea that, ultimately, people must heal themselves; (c) forgiveness – the notion that healing cannot progress if a person holds the burden of anger and pain; and (d) balance – the idea that it is possible to bring like and unlike things together in unity and harmony. The narratives revealed providers’ ontological assumptions about mind-body systems and the rationalities they seek to resist in their conversations with patients.

Human action recognition using simple geometric features and a finite state machine

2013 ◽  
Vol 18 (2-3) ◽  
pp. 49-60 ◽  
Author(s):  
Damian Dudzńiski ◽  
Tomasz Kryjak ◽  
Zbigniew Mikrut
Keyword(s):  
Action Recognition ◽  
Finite State Machine ◽  
Recognition Rate ◽  
Human Action Recognition ◽  
Human Action ◽  
Video Stream ◽  
State Machine ◽  
Recognition Algorithm ◽  
Finite State ◽  
Correct Recognition Rate

Abstract In this paper a human action recognition algorithm, which uses background generation with shadow elimination, silhouette description based on simple geometrical features and a finite state machine for recognizing particular actions is described. The performed tests indicate that this approach obtains a 81 % correct recognition rate allowing real-time image processing of a 360 X 288 video stream.

Deep Learning for Human Action Recognition Survey

2018 ◽  
Vol 6 (10) ◽  
pp. 323-328
Author(s):  
K.Kiruba . ◽  
D. Shiloah Elizabeth ◽  
C Sunil Retmin Raj
Keyword(s):  
Deep Learning ◽  
Action Recognition ◽  
Human Action Recognition ◽  
Human Action

Surgical Action Recognition with Spatiotemporal Convolutional Neural Networks

2019 ◽  
Author(s):  
Giacomo De Rossi ◽  
◽  
Nicola Piccinelli ◽  
Francesco Setti ◽  
Riccardo Muradore ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Action Recognition

Zastosowanie analizy sieci społecznych w badaniach elit parlamentarnych (na przykładzie eurodeputowanych z Polski)

2014 ◽  
pp. 8-24 ◽  
Author(s):  
Piotr Swacha
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
European Parliament ◽  
Political Groups ◽  
Graphical Presentation ◽  
Relational Network

The purpose of this article is to present the possibilities of using social network analysis (SNA) in the study of the European Parliament elite. This study focuses on organisational connections between Polish members of the European Parliament (seventh term). Official organisational relationships of Polish MEPs include common membership in: political groups, authorities of parliamentary committees and delegations, Parliament’s Bureau, Conference of Presidents, Conference of Committee (and Delegation) Chairs. UCInet and Netdraw programmes were used to calculate SNA’s basic measures and to prepare graphical presentation of relational network created by the Polish MEPs. On this basis main characteristics of the network were presented and MEPs who had the best network locations were distinguished.

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