Abnormal Action Recognition in Power Production

2011 ◽  
Vol 225-226 ◽  
pp. 311-314
Author(s):  
Zhen Hua Wei ◽  
Xue Sen Li ◽  
Jie Lin ◽  
Le Zhang
Keyword(s):  
Action Recognition ◽  
Power Production ◽  
Time Cost ◽  
Object Based ◽  
Specific Object ◽  
Effective Level ◽  
Interactive Relationship ◽  
Trajectory Features ◽  
Human Silhouette ◽  
Primitive Action

Safety is of importance for power production. It is known that kinds of abnormal action in power production are concerned with objects. Different from many abnormal action recognitions researches, which ignore the interactive relationship between human and objects, this paper proposes an approach for the specific abnormal action based objects recognition in power production. The major contributions of the paper are to employ an object-based framework for description of hand-trajectory information, reference particle filter for primitive action locating and realize time cost decrease through human silhouette block analysis. Different from simplex trajectory based approach, the presented approach consists of types of trajectory features which belong to specific object and each primitive action is relevant to specific object model. It is verified by experiment that the approach performs on certain abnormal action recognition at an effective level.

scholarly journals A Novel Class-Specific Object-Based Method for Urban Change Detection Using High-Resolution Remote Sensing Imagery

2021 ◽  
Vol 87 (4) ◽  
pp. 249-262
Author(s):  
Ting Bai ◽  
Kaimin Sun ◽  
Wenzhuo Li ◽  
Deren Li ◽  
Yepei Chen ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
High Resolution ◽  
Land Cover ◽  
Change Detection ◽  
Urban Areas ◽  
Support Vector ◽  
Change Type ◽  
Optimal Classifier ◽  
Object Based ◽  
Specific Object

A single-scale object-based change-detection classifier can distinguish only global changes in land cover, not the more granular and local changes in urban areas. To overcome this issue, a novel class-specific object-based change-detection method is proposed. This method includes three steps: class-specific scale selection, class-specific classifier selection, and land cover change detection. The first step combines multi-resolution segmentation and a random forest to select the optimal scale for each change type in land cover. The second step links multi-scale hierarchical sampling with a classifier such as random forest, support vector machine, gradient-boosting decision tree, or Adaboost; the algorithm automatically selects the optimal classifier for each change type in land cover. The final step employs the optimal classifier to detect binary changes and from-to changes for each change type in land cover. To validate the proposed method, we applied it to two high-resolution data sets in urban areas and compared the change-detection results of our proposed method with that of principal component analysis k-means, object-based change vector analysis, and support vector machine. The experimental results show that our proposed method is more accurate than the other methods. The proposed method can address the high levels of complexity found in urban areas, although it requires historical land cover maps as auxiliary data.

Action Recognition

2010 ◽  
pp. 228-243
Author(s):  
Qingdi Wei ◽  
Xiaoqin Zhang ◽  
Weiming Hu
Keyword(s):  
Action Recognition ◽  
Mean Shift ◽  
Human Action ◽  
Shape Context ◽  
Research Fields ◽  
Dominant Set ◽  
Novel Method ◽  
Active Research ◽  
Context Features ◽  
Human Silhouette

Action recognition is one of the most active research fields in computer vision. This chapter first reviews the action recognition methods in literature from two aspects: action representation and recognition strategy. Then, a novel method for classifying human actions from image sequences is investigated. In this method, each human action is represented by a sequence of shape context features of human silhouette during the action, and a dominant set-based approach is employed to classify the action to the predefined classes. The dominant set-based approach to classification is compared with K-means, mean shift, and Fuzzy-Cmean approaches.

scholarly journals Is There a Relationship between Energy, Amount of Information and Temperature?

2019 ◽  
pp. 1-9
Author(s):  
Boris M. Menin
Keyword(s):  
Information Theory ◽  
Ambient Temperature ◽  
Physical System ◽  
Scientific Literature ◽  
Energy Content ◽  
Thermodynamic Temperature ◽  
Amount Of Information ◽  
Object Based ◽  
Specific Object ◽  
The Universe

Aims: To use the generally accepted formulas linking energy, temperature and information, and not requiring any additional restrictions, to introduce a practical numerical value of the energy of any specific object based on the amount of information and thermodynamic temperature. Place and Duration of Study: Beer-Sheba, between January 2019 and July 2019. Methodology: By combining the Landauer limit and Bekenstein’s proof that the amount of information of any physical system must be finite, if the object space and its energy are finite, the values of energy-matter and energy, based on the amount of information, were calculated for various elements of nature. In addition, a formula is presented for the energy of the universe containing these two components. Results: The energy content of an object depends not only on its mass and speed. The value of the additional independent component, due to the amount of information contained in the object, is caused by its size and the ambient temperature. This component has never been considered in the scientific literature. This means that energy is inextricably linked with both the space and the thermodynamic component of Nature. Conclusion: Using the generally accepted formulas linking energy, temperature and information and not requiring any additional restrictions, we have shown that it is possible to represent the energy of the universe on the basis of information theory.

scholarly journals Sports Action Recognition Based on Image Processing Technology and Analysis of the Development of Sports Industry Pattern

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhaoyin Jiang ◽  
Fuyou Zhang ◽  
Laishuang Sun
Keyword(s):  
Image Processing ◽  
Action Recognition ◽  
Information Age ◽  
Industry Structure ◽  
Processing Technology ◽  
Visual Feature ◽  
Time Cost ◽  
Sports Industry ◽  
Image Processing Technology ◽  
Image Collection

The current era is an information age, and society is turning to the information age. The image processing technology is also widely used in various fields, and the technology of sports action recognition based on image processing technology can also be said to be appropriate. This article uses a spatial visual feature analysis algorithm to implement it. To implement this algorithm, a series of work such as image collection, feature extraction, and action recognition must be completed first and then implemented through texture functions and other related functions. This algorithm can be used to complete the image-based sports action recognition technology at the minimum time cost. This algorithm can help sportsmen better complete training and standardize movements to a certain extent. As for the development of China’s current sports industry structure, it is also steadily improving. The people’s love for sports is getting stronger and stronger, which also makes the development of China’s sports industry still benefit a lot.

scholarly journals Effects of cue validity on the temporal dynamics of attentional selection

2021 ◽  
Author(s):  
Hao Lou ◽  
Monicque Lorist ◽  
Karin S Pilz
Keyword(s):  
Temporal Dynamics ◽  
Large Individual ◽  
Group Level ◽  
Target Interval ◽  
Specific Location ◽  
Cue Validity ◽  
Object Based ◽  
Key Factor ◽  
Specific Object ◽  
Low Prevalence

Visual attention can be allocated to locations or objects, leading to enhanced processing of the specific location (space-based effects) or specific object (object-based effects). Object-based effects are smaller and less robust than space-based effects and prone to large individual differences. Moreover, the temporal dynamics of object-based effects have been found to differ largely between individuals. Studies on space- and object-based effects are often based on a two-rectangle paradigm with target distribution biased to the cued location. To assess whether and how the target's spatial probability modulates the temporal dynamics of attentional effects, we manipulated cue validity from 80% over 50% to 33% in three experiments. We investigated the temporal dynamics of space- and object-based effects on group level and for individual participants. We observed that the magnitude and the prevalence of space-based effects heavily decrease with reduced cue validity. The low prevalence of object-based effects did not change across experiments, as independent of cue validity, only a few participants showed significant effects in each cue-to-target interval. Our results highlight that cue validity is a key factor for the strength and prevalence of space-based effects but does not account for the low prevalence of object-based effects.

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