Detection of pedestrian crossing road

Hariyono, Joko; Jo, Kang-Hyun

doi:10.1109/icip.2015.7351675

Cited by 26 publications

(10 citation statements)

References 8 publications

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“…Based on this study, we know that counting human and detecting human presence can be implemented using this technique and it is suitable especially in the large area such as lecture hall and laboratory. [12] proposed to identify and localize the pedestrian from moving vehicle concerning road area and relative distance from the vehicle. They used the location classification to differentiate between the nonmoving background and moving foreground.…”

Section: B Location-based Person Detectionmentioning

confidence: 99%

Person Detection for Social Distancing and Safety Violation Alert based on Segmented ROI

Ahamad

Zaini

Latip

2020

2020 10th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)

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In addressing the worldwide Covid-19 pandemic situation, the process of flattening the curve for coronavirus cases will be difficult if the citizens do not take action to prevent the spread of the virus. One of the most important practices in these outbreaks is to ensure a safe distance between people in public. This paper presents the detection of people with social distance monitoring as a precautionary measure in reducing physical contact between people. This study focuses on detecting people in areas of interest using the MobileNet Single Shot Multibox Detector (SSD) object tracking model and OpenCV library for image processing. The distance will be computed between the persons detected in the captured footage and then compared to a fixed pixels' values. The distance is measured between the central points and the overlapping boundary between persons in the segmented tracking area. With the detection of unsafe distances between people, alerts or warnings can be issued to keep the distance safe. In addition to social distance measure, another key feature of the system is detecting the presence of people in restricted areas, which can also be used to trigger warnings. Some analysis has been performed to test the effectiveness of the program for both purposes. From the results obtained, the distance tracking system achieved between 56.5% to 68% accuracy for testing performed on outdoor and challenging input videos, while 100% accuracy was achieved for the controlled environment on indoor testing. Whereas for the safety violation alert feature based on segmented ROI, it was found to have achieved better accuracy, i.e. between 95.8% to 100% for all tested input videos.

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Section: B Location-based Person Detectionmentioning

confidence: 99%

Person Detection for Social Distancing and Safety Violation Alert based on Segmented ROI

Ahamad

Zaini

Latip

2020

2020 10th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)

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“…In this section, the proposed detection system is comparatively experimented with the latest seven detectors and three benchmark datasets. To validate our proposed system, we have tested it on four publicly available sequences, which are PET'09 S3.MF (multiple flow) and PET'09 S0.CC (city center) from the PET benchmark [20] , "Caltech Person" dataset from the California Institute of Technology dataset [21], and the INRIA Person dataset [22]. The first two datasets are consecutive frames captured by one fixed camera, while the sequences of the latter two datasets are chosen from different scenarios.…”

Section: Experiments and Analysismentioning

confidence: 99%

A Boosted 3-D PCA Algorithm Based on Efficient Analysis Method

Lee

Lin

2021

Applied Sciences

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In this paper, we propose a boosted 3-D PCA algorithm based on an efficient analysis method. The proposed method involves three steps that improve image detection. In the first step, the proposed method designs a new analysis method to solve the performance problem caused by data imbalance. In the second step, a parallel cross-validation structure is used to enhance the new analysis method further. We also design a modified AdaBoost algorithm to improve the detector accuracy performance of the new analysis method. In order to verify the performance of this system, we experimented with a benchmark dataset. The results show that the new analysis method is more efficient than other image detection methods.

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“…Hariyono and Jo [12] proposed to distinguish and restrict the person on foot from moving vehicles concerning the street region and relative separation from the vehicle. They utilized the area characterization to separate between the immobile foundation and moving closer view.…”

Section: Area-based Human Detectionmentioning

confidence: 99%

Social Distancing and Crowd Density Distribution System for Public Places and Public Transports Using Computer Vision and NLP

Sharma

Modanval

Tayal

et al. 2021

Advanced Computing and Intelligent Technologies

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The world population is growing day by day but the resources are limited. So, on one hand, we have to fulfill our requirements by using resources in an optimized manner, and on the other hand, we are currently in a pandemic for which social distancing is the key to prevent ourselves from the COVID-19 virus. We all travel by bus, train, metros, and other public transports, and we all have faced the problem of overcrowding in public transport once in our life especially during any festive season when there is a lot of rush among people to go from their workplace to their hometown. The problem of overcrowding is very common in developing countries like India where the population is relatively higher than the number of seats in public transports. For instance, if we look at the Delhi metro in which it is almost impossible to travel during the festive season. However, it's a regular problem, but the crowd becomes more when any festive season approaches. And due to such rush, people tend to just get inside the metro without even searching for a relatively less crowded or vacant seat/compartment, resulting in an unusual pattern of density seen across the metro, somewhere empty and somewhere highly crowded that even no place to stand. And now due to the COVID-19 pandemic, the situation worsens, on one hand, we are bound to travel in-crowd for work and on the other hand, we have to maintain social distancing for COVID prevention. So it becomes almost impossible to travel through such public transport. To solve such problems we are proposing a solution, that is, a system that takes care of the public places/transports by scanning and informing passengers where they can move to find a seat or less crowded. It also helps to ensure social distancing in the times of the COVID-19 pandemic.

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Detection of pedestrian crossing road

Cited by 26 publications

References 8 publications

Person Detection for Social Distancing and Safety Violation Alert based on Segmented ROI

Person Detection for Social Distancing and Safety Violation Alert based on Segmented ROI

A Boosted 3-D PCA Algorithm Based on Efficient Analysis Method

Social Distancing and Crowd Density Distribution System for Public Places and Public Transports Using Computer Vision and NLP

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