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Smartphones enable understanding human behavior with activity recognition to support people’s daily lives. Prior studies focused on using inertial sensors to detect simple activities (sitting, walking, running, etc.) and were mostly conducted in ...

Map applications on smartphones are powerful navigation tools for walking among places to visit for the first time and are widely used. On the other hand, checking the map applications tend to cause accidents on the road such as collisions with people, ...

A new smoking behavior recognition algorithm based on a weak supervision fine-grained structure and the EficientDet network is proposed in this study to solve the poor recognition effect and lack of data samples of smoking behavior in complex situations. ...

In order to solve the problems of low recognition accuracy and high computational complexity caused by redundant video data in the existing behavior recognition process, a human behavior recognition method based on video key frame (S3DCCA) is proposed. ...

Under the impact of COVID-19, research on behavior recognition are highly needed. In this paper, we combine the algorithm of self-adaptive coder and recurrent neural network to realize the research of behavior pattern recognition. At present, most of the ...

Fatigue driving is the primary cause of traffic accidents. Because fatigue detection has the characteristics of high real-time requirements and low complexity, shallow convolutional neural networks are often chosen as the deep learning framework for ...

Numerous behavior recognition researches have focused on UCF-101 video dataset, such as sports, cooking and other simple routines. Yet these studies are less useful in real-life surveillance scenarios. Violence detection in crowded scenes (such as ...

Time dynamics is a very important part of human behavior recognition. The linear dynamic system can model the time dynamics, but in the traditional linear dynamic system, the transfer matrix and the output matrix are subject to permutations, rotations, ...

Many HAR (Human Activity Recognition) systems are able to detect sequential executed ADL (Activity of Daily Living). While a person is capable of doing two things in parallel or to pause one ADL and finishing it later a HAR system (HARS) must be capable ...

User-centered design applied to non-human animals is showing to be a promising research line known as Animal Computer Interaction (ACI), aimed at improving animals' wellbeing using technology. Within this research line, intelligent systems for animal ...

With the development of Internet of Things (IOT) industry, research on wildlife monitoring meets with innovative progress. In this manuscript, we analyze the development of communication technologies, and discuss the architecture of wildlife observation ...

In this paper, we show an opportunistic sensing-based system for road anomaly detection. To detect road anomalies such as cracks, pits, and puddles, we focus on pedestrian's avoidance behavior that is characterized by the azimuth changing patterns. ...

Real-time, automatic detection of smoking behavior could lead to novel measurement tools for smoking research and "just-in-time" interventions that may help people quit, reducing preventable deaths. This paper discusses the use of machine learning with ...

Models of swarming and modes of controlling them are numerous; however, to date swarm researchers have mostly ignored a fundamental problem that impedes scalable human interaction with large bio-inspired robot swarms, namely, how do you know what the ...

Combat survivability is an important objective in military air operations, which involves not being shot down by e.g. enemy aircraft. This involves analyzing data and information, detecting and estimating threats, and implementing actions to counteract ...

In this paper we introduce a new descriptor, the Human Constrained Pixel Change History (HC-PCH), which is based on Pixel Change History (PCH) but focuses on the human body movements over time. We propose a modification of the conventional PCH which ...

To improve traditional video surveillance systems' performance on human behavior recognition, a new system has been built. Not visual camera but depth camera is chosen as sensor. To adapt to the most common forward oblique view of camera, a normalized ...

We introduce a new mobile system framework, SenSec, which uses passive sensory data to ensure the security of applications and data on mobile devices. SenSec constantly collects sensory data from accelerometers, gyroscopes and magnetometers and ...

Reliable estimation of number of pedestrians has played an important role in the management of public places. However, how to accurately count pedestrians with abnormal behavior noises is one challenge in such surveillance systems. To deal with this ...

Since the endless new networking applications and security issues, it's urgent for governments, corporations and ISPs to identify, classify and control the network flows. Comparing with DPI technologies, flow-based behavior recognition has advantages of ...