Human Behavior Classification Using Geometrical Features of Skeleton and Support Vector Machines

Classification of human actions under video surveillance is gaining a lot of attention from computer vision researchers.In this paper,we have presented methodology to recognize human behavior in thin crowd which may be very helpful in surveillance.Research have mostly focused the problem of human detection in thin crowd,overall behavior of the crowd and actions of individuals in video sequences.Vision based Human behavior modeling is a complex task as it involves human detection,tracking,classifying normal and abnormal behavior.The proposed methodology takes input video and applies Gaussian based segmentation technique followed by post processing through presenting hole filling algorithm i.e.,fill hole inside objects algorithm.Human detection is performed by presenting human detection algorithm and then geometrical features from human skeleton are extracted using feature extraction algorithm.The classification task is achieved using binary and multi class support vector machines.The proposed technique is validated through accuracy,precision,recall and F-measure metrics.

Study on Local Optical Flow Method Based on YOLOv3 in Human Behavior Recognition

In the process of human behavior recognition, the traditional dense optical flow method has too many pixels and too much overhead, which limits the running speed. This paper proposed a method combing YOLOv3 (You Only Look Once v3) and local optical flow method. Based on the dense optical flow method, the optical flow modulus of the area where the human target is detected is calculated to reduce the amount of computation and save the cost in terms of time. And then, a threshold value is set to complete the human behavior identification. Through design algorithm, experimental verification and other steps, the walking, running and falling state of human body in real life indoor sports video was identified. Experimental results show that this algorithm is more advantageous for jogging behavior recognition.

An Event Alarm System Based on Single and Group Human Behavior Analysis

Due to the increasing demand for security, the development of intelligent surveillance systems has attracted considerable attention in recent years. This study aims to develop a system that is able to identify whether or not the people need help in a public place. Different from previous work, our work considers not only the behaviors of the target person but also the interaction between him and nearby people. In the paper, we propose an event alarm system which can detect the human behaviors and recognize the happening event through integrating the results generated from the single and group behavior analysis. Several new effective features are proposed in the study. Besides, a mechanism capable of extracting one-to-one and multiple-to-one relations is also developed. Experimental results show that the proposed approach can correctly detect human behaviors and provide the alarm messages when emergency events occur.

Environment and Human Behaviors——Taking “The Acorn Gatherer” as a Case Study

Human living environment interacts with human behaviors.Environment to some degree determines human behaviors which in return reshape and sustain the dynamic environment.Taking Richard Jefferies' The Acorn Gatherer as a case study,this paper makes an argument that the behaviors of the villagers in the story can be more adequately interpreted in view of the backward countryside environment,and the same is true with the author Richard Jefferies' non-interference in the omniscient third-person point of view in writing the story.It is Richard Jefferies' family environment that makes up his viewpoint of writing,reflecting his critical loving of the countryside,where lives boom and conventions are extremely followed.

Ecological Environment in Terms of Human Behavior

In terms of human behavior,company and government policy,it is proposed that the ecological behavior of human being is the basis of influence on the ecological environment construction in Poyang Lake and measures to ensure the sustainable development of ecological environment in Poyang Lake.

Image Semantic Segmentation Approach for Studying Human Behavior on Image Data

Image semantic segmentation is an essential technique for studying human behavior through image data.This paper proposes an image semantic segmentation method for human behavior research.Firstly,an end-to-end convolutional neural network architecture is proposed,which consists of a depth-separable jump-connected fully convolutional network and a conditional random field network;then jump-connected convolution is used to classify each pixel in the image,and an image semantic segmentation method based on convolu-tional neural network is proposed;and then a conditional random field network is used to improve the effect of image segmentation of hu-man behavior and a linear modeling and nonlinear modeling method based on the semantic segmentation of conditional random field im-age is proposed.Finally,using the proposed image segmentation network,the input entrepreneurial image data is semantically segmented to obtain the contour features of the person;and the segmentation of the images in the medical field.The experimental results show that the image semantic segmentation method is effective.It is a new way to use image data to study human behavior and can be extended to other research areas.

Earth surface processes and their effects on human behavior in monsoonal China during the Pleistocene-Holocene epochs

There is a wide diversity of landforms in China. The topography of three major ter- races, decreasing in height stepwise from west to east, was formed by the early Miocene. With the commencement of the Great Northern Hemisphere Glaciations （GHGs） and the glacial-interglacial cycles in the Pleistocene, thick loess deposits accumulated in north China, and fluvial terraces were formed and lakes expanded and contracted in eastern and central China. The earliest evidence of hominins in China is dated to ~1.7 Ma; they occupied the monsoon-dominated region for a long interval, until the late Pleistocene, ~50 ka. In this study, we investigated a large area rich in the relics and artifacts of early man. The results indicate that the early humans occupied riverine areas, especially medium-sized fluvial basins, and lake shores. Even in the relatively recent geological past, the occupation and abandonment of settlements were directly forced by the shifting of sand dune fields in the desert-loess transi- tional zone, which in turn was closely associated with variations in the monsoon climate and vegetation patterns. Our observations indicate that landforms were one of the main determi- nants of early human behavior, in that loess tableland, large alluvial plains, desert-Gobi areas, and the Tibetan Plateau, were not suitable environments for early human settlement. We infer that the early humans in China adapted their behavior to specific landforms and landform processes. The monsoon climate, which shapes the large-scale step-like pattern of fluvial landforms, promotes vegetation coverage and dominates soil formation, provides a crucial context for early human adaptation. The adaptation of early humans to earth surface proc- esses in East Asia is investigated for the first time in this study. Future investigations will provide further information that will increase our understanding of the linkage between early human behavior and landform processes in East Asia.

Integrated design of transport infrastructure and public spaces considering human behavior:A review of state-of-the-art methods and tools

In order to achieve holistic urban plans incorporating transport infrastructure,public space and the behavior of people in these spaces,integration of urban design and computer modeling is a promising way to provide both qualitative and quantitative support to decisionmakers.This paper describes a systematic literature review following a four-part framework.Firstly,to understand the relationship of elements of transport,spaces,and humans,w e review policy and urban design strategies for promoting positive interactions.Secondly,we present an overview of the integration methods and strategies used in urban design and policy discourses.Afterward,metrics and approaches for evaluating the effectiveness of integrated plan alternatives are reviewed.Finally,this paper gives a review of state-of-the-art tools with a focus on seven com puter simulation paradigms.This article explores mechanisms underlying the complex system of transport,spaces,and humans from a multidisciplinary perspective to provide an integrated toolkit for designers,planners,modelers and decision-m akers with the current methods and their challenges.

Behavior Recognition of the Elderly in Indoor Environment Based on Feature Fusion of Wi-Fi Perception and Videos

With the intensifying aging of the population,the phenomenon of the elderly living alone is also increasing.Therefore,using modern internet of things technology to monitor the daily behavior of the elderly in indoors is a meaningful study.Video-based action recognition tasks are easily affected by object occlusion and weak ambient light,resulting in poor recognition performance.Therefore,this paper proposes an indoor human behavior recognition method based on wireless fidelity(Wi-Fi)perception and video feature fusion by utilizing the ability of Wi-Fi signals to carry environmental information during the propagation process.This paper uses the public WiFi-based activity recognition dataset(WIAR)containing Wi-Fi channel state information and essential action videos,and then extracts video feature vectors and Wi-Fi signal feature vectors in the datasets through the two-stream convolutional neural network and standard statistical algorithms,respectively.Then the two sets of feature vectors are fused,and finally,the action classification and recognition are performed by the support vector machine(SVM).The experiments in this paper contrast experiments between the two-stream network model and the methods in this paper under three different environments.And the accuracy of action recognition after adding Wi-Fi signal feature fusion is improved by 10%on average.

The modelling and application of cross-scale human behavior in realizing the shop-floor digital twin[version 1;peer review:1 approved with reservations,1 not approved]

The digital twin shop-floor has received much attention from the manufacturing industry as it is an important way to upgrade the shop-floor digitally and intelligently.As a key part of the shop-floor,humans'high autonomy and uncertainty leads to the difficulty in digital twin modeling of human behavior.Therefore,the modeling system for cross-scale human behavior in digital twin shop-floors was developed,powered by the data fusion of macro-behavior and micro-behavior virtual models.Shop-floor human macro-behavior mainly refers to the role of the human and their real-time position.Shop-floor micro-behavior mainly refers to real-time human limb posture and production behavior at their workstation.In this study,we reviewed and summarized a set of theoretical systems for cross-scale human behavior modeling in digital twin shop-floors.Based on this theoretical system,we then reviewed modeling theory and technology from macro-behavior and micro-behavior aspects to analyze the research status of shop-floor human behavior modeling.Lastly,we discuss and offer opinion on the application of cross-scale human behavior modeling in digital twin shop-floors.Cross-scale human behavior modeling is the key for realizing closed-loop interactive drive of human behavior in digital twin shop-floors.

Human Activity Recognition Based on Frequency-Modulated Continuous Wave and DenseNet

With the development of wireless technology, Frequency-Modulated Continuous Wave (FMCW) radar has increased sensing capability and can be used to recognize human activity. These applications have gained wide-spread attention and become a hot research area. FMCW signals reflected by target activity can be collected, and human activity can be recognized based on the measurements. This paper focused on human activity recognition based on FMCW and DenseNet. We collected point clouds from FMCW and analyzed them to recognize human activity because different activities could lead to unique point cloud features. We built and trained the neural network to implement human activities using a FMCW signal. Firstly, this paper presented recent reviews about human activity recognition using wireless signals. Then, it introduced the basic concepts of FMCW radar and described the fundamental principles of the system using FMCW radar. We also provided the system framework, experiment scenario, and DenseNet neural network structure. Finally, we presented the experimental results and analyzed the accuracy of different neural network models. The system achieved recognition accuracy of 100 percent for five activities using the DenseNet. We concluded the paper by discussing the current issues and future research directions.

Modern human behaviors during the late stage of the MIS3 and the broad spectrum revolution:Evidence from a Shuidonggou Late Paleolithic site

The last glacial period was vital for the distribution and evolution of early modern humans in Asia. The Shuidonggou Late Paleolithic site, dated at 30-20 ka BP, accumulated cultural remains during the important late stage of MIS 3 period in the last glacial. These remains represent characteristics of typical Late Paleolithic conditions in North China:high degree of standardization and morphological variability of tool types, exploitation of bone materials, systematic use of body decorations, extensive use of earth-pit hearths, distinct functional spatial organization within habitations, and conversion of subsistence patterns. These characteristics illustrate early modern human behaviors during the late MIS3 period, and provide clues and perspectives for the analysis of early modern human origins in China. At the same time, the conversion of subsistence patterns is considered to be a combination of multiple early modern human behaviors, as well as the result of the Broad Spectrum Revolution. In this paper, we argue for the dynamic mechanism of Broad Spectrum Revolution from a human behavioral and ecological perspective.

Mortality profiles of the large herbivores from the Lingjing Xuchang Man Site,Henan Province and the early emergence of the modern human behaviors in East Asia

This paper presents the results of a detailed study of mortality profiles of the large herbivores from the Middle Palaeolithic (MP) bone assemblage of the Lingjing Xuchang Man Site, Henan Province. Based on the analysis of the crown heights of fossil teeth from this assemblage, we come to a conclusion that aurochs (Bos primigenius) and horse (Equus caballus) are the major prey species in this assemblage and the age structures of these animals can be best described as the "prime-dominated pattern". This study confirmed the well-established notions at many Middle and Upper Palaeolithic sites across Eurasia and Africa that MSA/MP foragers were fully effective in hunting aggressive prey species, particularly aurochs and horse. This find indicates that the hunting behaviors and subsistence strategies were not significantly different between MP and UP (the Upper Palaeolithic) humans in East Asia and hence suggests the early emergence of the modern human behaviors in this area.

Heat treatment and associated early modern human behaviors in the Late Paleolithic at the Shuidonggou site

Unearthed artifacts and cultural relics from the Shuidonggou site revealed extensive information and insights regarding the activities of early modern humans.A series of experimental research and physical analysis suggest that stone artifacts from Locality 2 and Locality 12 have undergone heat treatment.The utilization ratio and knapping properties of raw materials were consequently enhanced.Heat treatment technology reflects the production capacities and the survival strategies in the Upper Paleolithic period.This discovery indicates the earliest existence of this technology in the East Asia and thus confirms a wider geographic distribution of this technology which provides new perspectives and evidence for understanding the associated early modern human behaviors.

Biological behaviors of two novel syngeneic human osteosarcoma cell lines

Objective To characterize and compare the different biological behaviors of two novel human osteosarcoma cell lines,Zos and Zos-M,established respectively from the primary site and the skip metastasis of an osteosarcoma patient.Methods Two

Associations among depression, suicidal behavior, and quality of life in patients with human immunodeficiency virus

AIM: To investigate the potential associations among major depression, quality of life, and suicidal behavior in human immunodeficiency virus(HIV) patients. METHODS: A detailed MEDLINE search was carried out to identify all articles and book chapters in English published from January 1995 to January 2015. RESULTS: Based on the main findings, the prevalence of major depressive disorder(MDD) ranged from 14.0% to 27.2%. Furthermore, the prevalence of suicidal ideation varied from 13.6% to 31.0% whereas, attempted suicides were reported to range from 3.9% to 32.7%. Interestingly, various associated risk factors for both depression and suicide were identified in HIV patients. Finally, consistent associations were reported among MDD, suicidal ideation, and poor quality of life in individuals living with HIV. CONCLUSION: Although additional studies are needed to elucidate this complex association, our results suggest the importance of early detection of both MDD and suicidality in patients living with HIV.