scholarly journals Extract the Relational Information of Static Features and Motion Features for Human Activities Recognition in Videos

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Li Yao
Keyword(s):  
Bipartite Graph ◽  
Human Activities ◽  
Recognition Task ◽  
Small Dimension ◽  
Relational Information ◽  
Kl Divergence ◽  
Motion Features ◽  
Projective Function ◽  
Human Activities Recognition ◽  
The Relationship

Both static features and motion features have shown promising performance in human activities recognition task. However, the information included in these features is insufficient for complex human activities. In this paper, we propose extracting relational information of static features and motion features for human activities recognition. The videos are represented by a classical Bag-of-Word (BoW) model which is useful in many works. To get a compact and discriminative codebook with small dimension, we employ the divisive algorithm based on KL-divergence to reconstruct the codebook. After that, to further capture strong relational information, we construct a bipartite graph to model the relationship between words of different feature set. Then we use ak-way partition to create a new codebook in which similar words are getting together. With this new codebook, videos can be represented by a new BoW vector with strong relational information. Moreover, we propose a method to compute new clusters from the divisive algorithm’s projective function. We test our work on the several datasets and obtain very promising results.

scholarly journals A Deep Learning Approach for Human Activities Recognition From Multimodal Sensing Devices

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 179028-179038
Author(s):  
Isibor Kennedy Ihianle ◽  
Augustine O. Nwajana ◽  
Solomon Henry Ebenuwa ◽  
Richard I. Otuka ◽  
Kayode Owa ◽  
...  
Keyword(s):  
Deep Learning ◽  
Human Activities ◽  
Learning Approach ◽  
Multimodal Sensing ◽  
Human Activities Recognition

scholarly journals Daily Human Activities Recognition Using Heterogeneous Sensors from Smartphones

2017 ◽  
Vol 111 ◽  
pp. 323-328 ◽  
Author(s):  
Minh-Son Dao ◽  
Tuan-Anh Nguyen-Gia ◽  
Van-Cuong Mai
Keyword(s):  
Human Activities ◽  
Heterogeneous Sensors ◽  
Human Activities Recognition

scholarly journals MORPHOLOGICAL MOMENTS OF BINARY IMAGES

2017 ◽  
Vol XLII-2/W4 ◽  
pp. 19-25
Author(s):  
N. Lomov ◽  
S. Sidyakin
Keyword(s):  
Radial Function ◽  
Recognition Task ◽  
Shape Descriptor ◽  
Computationally Efficient ◽  
Binary Images ◽  
Integral Width ◽  
Recognition Quality ◽  
Font Recognition ◽  
The Relationship ◽  
Exact Analytical Method

The concept of morphological moments of binary images is introduced. Morphological moments can be used as a shape descriptor combining an integral width description of an object with a description of its spatial distribution. The relationship between the proposed descriptor and the disc cover of the figure is discussed and an exact analytical method for descriptor calculation is proposed within the continuous morphology framework. The approach is based on the approximation of the shape by a polygonal figure and the extraction of its medial representation in the form of the continuous skeleton and the radial function. The proposed method for calculation of morphological moments achieves high accuracy and it is computationally efficient. Experimentations have been conducted. Obtained results indicate that the morphological moments are a more informative and rich shape descriptor than the area of the disc cover. Application of morphological moments to the font recognition task improves the recognition quality.

scholarly journals Seismicity and development of Romashkino hydrocarbon field’s Almetyevskaya area

Georesursy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 51-57
Author(s):  
Igor Ognev ◽  
Alexey Stepanov
Keyword(s):  
Human Activities ◽  
Active Zone ◽  
Seismic Activity ◽  
The South ◽  
South Eastern ◽  
Hydrocarbon Fields ◽  
The Relationship ◽  
Hydrocarbon Field

The relationship between the various human activities and seismic activity has become more evident in the last several decades. One of the important domains where such a relationship manifests itself is hydrocarbon fields’ development. South East Tatarstan (Russia) is a region where the link between seismicity and the development of the giant Romashkino hydrocarbon field has been established. The goal of the current study is to conduct the causative analysis between the seismic activity and the development of the Romashkino hydrocarbon field’s Almetyevskaya area which is located in the most seismically active zone of the south-eastern Tatarstan.

scholarly journals Investigating the relationship between Psychopathy, Fear Conditioning, and Facial Affect Recognition

2021 ◽  
Author(s):  
◽  
Allanah R. Casey
Keyword(s):  
Fear Conditioning ◽  
Recognition Task ◽  
Psychopathic Traits ◽  
Facial Affect ◽  
Inhibition Mechanism ◽  
Affect Recognition ◽  
Facial Affect Recognition ◽  
Present Sample ◽  
Student Sample ◽  
The Relationship

<p>Psychopathic offenders are often considered to be untreatable, especially dangerous, and at very high risk of reoffending. Psychopathy has generated considerable research interest. Despite this interest, our understanding of psychopathy is relatively poor, with ongoing debate regarding how best to define psychopathy, and a lack of clarity regarding how psychopathy develops. Etiological theories of psychopathy posit deficits in recognising and responding to others’ emotions, and an attenuated experience of fear as crucial mechanisms in the development of psychopathy. The aims of this thesis are to investigate the pattern of psychopathic traits present within an inmate sample, and to investigate the relationship between these psychopathic traits and performance on two tasks related to etiological theories of psychopathy: facial affect recognition and fear conditioning. Part One of this thesis addresses the first aim, investigating the presentation of psychopathy in the current sample. The relationship between psychopathic traits in the present sample was largely consistent with previous research. A Principal Components Analysis identified two factors of psychopathic traits: a Bold/ Fearlessness factor which measures an absence of fear and anxiety and the presence of self-assurance, and a Mean/ Disinhibited factor which measures the presence of externalising and disinhibited behaviour, alongside aggression and the use of other people for one’s own gain. These findings are discussed in relation to common conceptualisations and operationalisations of psychopathy.   Part Two of this thesis uses the measurement of psychopathy from Part One to investigate performance on a facial affect recognition task and a fear conditioning task. The Violence Inhibition Mechanism theory suggests that psychopaths should show impairments on facial affect recognition tasks, particularly in the recognition of fearful and sad facial expressions. However, in the current research psychopathy was unrelated to affect recognition, across all emotional expressions. When criminal offenders were compared to a student sample, the offenders showed poorer affect recognition than the students. These results suggest that there may be an effect of antisociality on affect recognition, but no effect of psychopathy. Low fear theories of psychopathy suggest that psychopaths should be impaired at learning conditioned fear associations. However, the present study found no evidence of psychopathy-related deficits in fear conditioning. Rather, higher psychopathy was related to better fear conditioning, with higher scores on the Mean/ Disinhibited factor predicting better discrimination between the conditioned and neutral stimuli.   Taken together, these findings suggest that psychopathy was not related to deficits in either affect recognition or fear conditioning. These findings are inconsistent with etiological theories of psychopathy, and question common assumptions about the deficits which characterise psychopathy.</p>

scholarly journals Cognitive and physiological measures of listening effort during degraded speech perception: A comparison of dual-task and pupillometry paradigms

2020 ◽  
Author(s):  
Sarah Elizabeth Margaret Colby ◽  
Bob McMurray
Keyword(s):  
Speech Perception ◽  
Dual Task ◽  
Pupil Size ◽  
Spoken Word Recognition ◽  
Recognition Task ◽  
Spoken Word ◽  
Physiological Measures ◽  
Listening Effort ◽  
Response Feedback ◽  
The Relationship

Purpose: Listening effort is quickly becoming an important metric for assessing speech perception in less-than-ideal situations. However, the relationship between the construct of listening effort and the measures used to assess it remain unclear. We compared two measures of listening effort: a cognitive dual task and a physiological pupillometry task. We sought to investigate the relationship between these measures of effort and whether engaging effort impacts speech accuracy.Method: In Experiment 1, 30 participants completed a dual task and pupillometry task that were carefully matched in stimuli and design. The dual task consisted of a spoken word recognition task and a visual match-to-sample task. In the pupillometry task, pupil size was monitored while participants completed a spoken word recognition task. Both tasks presented words at three levels of listening difficulty (unmodified, 8-channel vocoding, and 4-channel vocoding) and provided response feedback on every trial. We refined the pupillometry task in Experiment 2 (n=31); crucially, participants no longer received response feedback. Finally, we ran a new group of subjects on both tasks in Experiment 3 (n=30).Results: In Experiment 1, accuracy in the visual task decreased with increased listening difficulty in the dual task, but pupil size was sensitive to accuracy and not listening difficulty. After removing feedback in Experiment 2, changes in pupil size were predicted by listening difficulty, suggesting the task was now sensitive to engaged effort. Both tasks were sensitive to listening difficulty in Experiment 3, but there was no relationship between the tasks and neither task predicted speech accuracy.Conclusions: Consistent with previous work, we found little evidence for a relationship between different measures of listening effort. We also found no evidence that effort predicts speech accuracy, suggesting that engaging more effort does not lead to improved speech recognition. Cognitive and physiological measures of listening effort are likely sensitive to different aspects of the construct of listening effort.

The Relationship of Indonesian Languange Learning with the Environment. Andriyani Muliana

2021 ◽  
Author(s):  
Andriyani Muliana
Keyword(s):  
Quality Of Life ◽  
Human Behavior ◽  
Environmental Conditions ◽  
Human Activities ◽  
Human Life ◽  
Common Environment ◽  
Relationship Of ◽  
The Relationship

The environment is closely related to nature and its creation. Problems faced by humans related to environmental conditions are things that have a big impact. The influence of the environment is very large on human life which makes the benchmark for good or bad human behavior. Because human life depends on the circumstances around him. Problems are often new things, but the things we often encounter in the environment are a variety of problems, such as the most common environment. According to Tung and Wihardjo (in Ramadhan et al, 2019), problems that occur in the environment caused by careless and intensive human activities in the area where he lives, this is done to improve the quality of life of each. Humans are more selfish without the environment when doing things that damage the environment. Whereas the consequences of their own actions will cause various impacts that are detrimental to themselves and others, such as floods that occur due to waste.

Recognizing Human Actions in Basketball Video Sequences on the Basis of Global and Local Pairwise Representation

2018 ◽  
pp. 2083-2101
Author(s):  
Masaki Takahashi ◽  
Masahide Naemura ◽  
Mahito Fujii ◽  
James J. Little
Keyword(s):  
Feature Representation ◽  
Video Sequences ◽  
Human Actions ◽  
The Public ◽  
Motion Features ◽  
Spatio Temporal ◽  
Representation Method ◽  
Global And Local ◽  
The Relationship ◽  
Local Representations

A feature-representation method for recognizing actions in sports videos on the basis of the relationship between human actions and camera motions is proposed. The method involves the following steps: First, keypoint trajectories are extracted as motion features in spatio-temporal sub-regions called “spatio-temporal multiscale bags” (STMBs). Global representations and local representations from one sub-region in the STMBs are then combined to create a “glocal pairwise representation” (GPR). The GPR considers the co-occurrence of camera motions and human actions. Finally, two-stage SVM classifiers are trained with STMB-based GPRs, and specified human actions in video sequences are identified. An experimental evaluation of the recognition accuracy of the proposed method (by using the public OSUPEL basketball video dataset and broadcast videos) demonstrated that the method can robustly detect specific human actions in both public and broadcast basketball video sequences.

Sign in / Sign up

Export Citation Format

Share Document