Vision-Based Safety Vest Detection in a Construction Scene

Abstract

The computer vision-based detection of construction workers in images or videos is necessary for the safety managements and productivity of construction workers. Researchers in previous studies, detecting construction workers in the construction scene via computer vision techniques, have considered various features such as motion, shape, and color. Due to the pose changes of the workers, construction worker detection using body shape as a feature in the construction scene remains a challenging task. This study proposes a safety vest detection method, as a preceding method of the construction worker detection, which uses the motion of workers and the color pixels of safety vests for distinguishing from others in the construction scene independent of the workers' pose changes. The background subtraction method is performed by using an approximate median filter for the purpose of reducing the candidate regions that the color pixel classification will be performed as a sequential step. Then, the color pixel classification method is performed with a comparative analysis of two color spaces (Lab and HSV

Machine-learning-based top-view safety monitoring of ground workforce on complex industrial sites

“…The videos were shortened to videos of 1-min length by removing the repetitive, unuseful frames. Totally 42,462 frames were extracted from the aforementioned scenes (bookstore (12,304), death circle (5,513), hyang (18,404) and little (6,247)). Three classes of objects (pedestrian, Biker and car) were selected for comparison.…”

“…The main methods adopted in top-view human detection are traditional and deep-learning techniques. In traditional methods, features such as hard-hat or high visibility jackets are detected [11,12] rather than performing directly human detection. Deep learning-based techniques have also been explored focusing more on direct human detection techniques [2,13].…”

Sistema automatizado para monitorear el uso de equipos de protección personal en la industria de la construcción

“…En laúltima década, la detección de EPP ha sido utilizada como filtro inicial en procesos de seguimiento visual de trabajadores en sitios de construcción. Este filtro es un clasificador de personas trabajadoras basado en la hipótesis de que todo trabajador objetivo debe utilizar ropa de alta visibilidad (Park and Brilakis, 2016;Seong et al, 2017;Mosberger et al, 2014;Konstantinou et al, 2019). La clasificación de estos EPP se materializa mediante detectores de color, que pueden diseñarse en distintos modelos como RGB, HSV o Lab, para determinar en una imagen la existencia de objetos con colores de seguridad conocidos (Park and Brilakis, 2016;Seong et al, 2017;Konstantinou et al, 2019;Mosberger et al, 2014).…”

“…Sin embargo, aunque el reconocimiento de EPP basado en descriptores visuales puede funcionar bien en situaciones controladas, en el marco operativo de la industria de la construcción, el entorno de trabajo habitual genera importantes dificultades (Xie et al, 2018). En imágenes tomadas en exteriores, los descriptores visuales asociados a EPP pueden sufrir alteraciones relevantes debidas a factores no evitables como la postura del trabajador respecto al punto de observación, la iluminación del entorno de trabajo y las oclusiones visuales debidas a otros trabajadores y sus herramientas de trabajo, entre otros (Seong et al, 2017;Mosberger et al, 2014). Esta situación es similar a la que ocurre en muchos otros contextos donde tradicionalmente se ha aplicado la ingeniería de atributos para entrenar sistemas de CV para propósitos diversos.…”

Robotics in the Construction Industry: State of the Art and Future Opportunities

“…On the other hand, as far as research topics are concerned, construction-related contributions have explored both consolidated and recent topics in the robotics field: inverse kinematics calculations [25,26], control architectures [27,28,29], trajectory planning algorithms [30], teleoperation strategies [31,32], Human-Machine Interfaces (HMIs) [33,34], autonomous vision [35,36], [37], usage of Unmanned Aerial Vehicles (UAVs) [38]. Another topic that is worth mentioning is represented by the integration with Building Information Modelling (BIM) [39,40,41].…”