Wyniki wyszukiwania - BazTech

1

Crowd Size Estimation and Detecting Social Distancing using Raspberry Pi and OpenCV

Milton Davidson Kamala Dhas, Velraj Arun Ra

International Journal of Electronics and Telecommunications

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2023

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Vol. 69, No. 1

19--24

EN

In this covid19 pandemic the number of people gathering at public places and festivals are restricted and maintaining social distancing is practiced throughout the world. Managing the crowd is always a challenging task. It requires monitoring technology. In this paper, we develop a device that detects and provide human count and detects people who are not maintaining social distancing. The work depicted above was finished using a Raspberry Pi 3 board with OpenCV-Python. This method can effectively manage crowds.

2

Detection of human faces in thermal infrared images

Kowalski Marcin Ł., Grudzień Artur, Ciurapiński Wiesław

Metrology and Measurement Systems

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2021

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Vol. 28, nr 2

307--321

EN

The presented study concerns development of a facial detection algorithm operating robustly in the thermal infrared spectrum. The paper presents a brief review of existing face detection algorithms, describes the experiment methodology and selected algorithms. For the comparative study of facial detection three methods presenting three different approaches were chosen, namely the Viola-Jones, YOLOv2 and Faster-RCNN. All these algorithms were investigated along with various configurations and parameters and evaluated using three publicly available thermal face datasets. The comparison of the original results of various experiments for the selected algorithms is presented.

3

Human safety in autonomous transport systems – review and case study

Dąbrowska Alicja, Giel Robert, Werbińska-Wojciechowska Sylwia

Journal of KONBiN

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2021

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Vol. 51, iss. 1

57--71

EN

During the robot's operational tasks, a key issue is its reliability in the aspect of human safety providing. Currently, there are a number of methods used to detect people, and their selection most often depends on the type of process carried out by robots. Therefore, the article is focused on the development of a comparative analysis of selected methods of human detection in the storage area. The main aspect in the context of which these systems were compared concerned the safety of robotic systems in the space of human occurrence. Main advantages and drawbacks of the methods in various applications were presented. The detailed analysis of the achievements in this area gives the possibility to identify research gaps and possible future research directions when using these tools in autonomous warehouses designing processes.

PL

Podczas wykonywania zadań operacyjnych przez robota, kluczowym zagadnieniem jest jego niezawodność w aspekcie bezpieczeństwa człowieka. Opracowano szereg metod służących do wykrywania człowieka, a ich wybór najczęściej uzależniony jest od rodzaju procesu realizowanego przez roboty. W związku z tym, celem artykułu jest przeprowadzenie analizy porównawczej wybranych metod wykrywania człowieka w strefie magazynowej. Główny aspekt, w kontekście którego dokonano porównania tych systemów dotyczył bezpieczeństwa pracy systemów robotycznych w przestrzeni występowania człowieka. Wskazano główne zalety i wady wybranych metod w różnych zastosowaniach. Szczegółowa analiza osiągnięć w tym obszarze dała możliwość zidentyfikowania luk badawczych i możliwych dalszych kierunków badań dotyczących wykorzystania tych narzędzi w projektowaniu procesów autonomicznych magazynów.

4

Histogram of Oriented Gradients with Cell Average Brightness for Human Detection

Wójcikowski M.

Metrology and Measurement Systems

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2016

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Vol. 23, nr 1

27--36

EN

A modification of the descriptor in a human detector using Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) is presented. The proposed modification requires inserting the values of average cell brightness resulting in the increase of the descriptor length from 3780 to 3908 values, but it is easy to compute and instantly gives ≈ 25% improvement of the miss rate at 10‒4 False Positives Per Window (FPPW). The modification has been tested on two versions of HOG-based descriptors: the classic Dalal-Triggs and the modified one, where, instead of spatial Gaussian masks for blocks, an additional central cell has been used. The proposed modification is suitable for hardware implementations of HOG-based detectors, enabling an increase of the detection accuracy or resignation from the use of some hardware-unfriendly operations, such as a spatial Gaussian mask. The results of testing its influence on the brightness changes of test images are also presented. The descriptor may be used in sensor networks equipped with hardware acceleration of image processing to detect humans in the images.

5

Human Detection in Thermal Images Using Low-level Features

Budzan S.

Measurement Automation Monitoring

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2015

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Vol. 61, No. 6

191--194

EN

In this work the human detection method in infrared has been presented. The proposed solution focuses on the use low-level features and detecting parts of the human body. Low–level processing is based on modified HOG (Histogram of Oriented Gradients) algorithm. First, the only squared cells have been used, also calculation of the gradient has been improved. Next, the model of the head from the dataset IR (Infra Red) images has been created, also the model of the human body. Finally, the probability matrix has been examined using minimal distance classifier. The novelty of the proposed solution focuses on the combination of the pixel-gradient and body parts processing, also three stage classification process (head modelling, human modelling and classifier), which has been proposed to reduce the false detection. The experiments were performed on self-created IR images database, which contains images with most of the possible difficult situations such as overlapped people, different pose, small and high resolution of the people. The performance of the proposed algorithm was evaluated using Precision and Recall quality measure.