Fusion Object Detection and Action Recognition to Predict Violent Action
In the context of Shared Autonomous Vehicles, the need to monitor the environment inside the car will be crucial. This article focuses on the application of deep learning algorithms to present a fusion monitoring solution which was three different algorithms: a violent action detection system, which...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/12/5610 |
| _version_ | 1797592631526555648 |
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| author | Nelson R. P. Rodrigues Nuno M. C. da Costa César Melo Ali Abbasi Jaime C. Fonseca Paulo Cardoso João Borges |
| author_facet | Nelson R. P. Rodrigues Nuno M. C. da Costa César Melo Ali Abbasi Jaime C. Fonseca Paulo Cardoso João Borges |
| author_sort | Nelson R. P. Rodrigues |
| collection | DOAJ |
| description | In the context of Shared Autonomous Vehicles, the need to monitor the environment inside the car will be crucial. This article focuses on the application of deep learning algorithms to present a fusion monitoring solution which was three different algorithms: a violent action detection system, which recognizes violent behaviors between passengers, a violent object detection system, and a lost items detection system. Public datasets were used for object detection algorithms (COCO and TAO) to train state-of-the-art algorithms such as YOLOv5. For violent action detection, the MoLa InCar dataset was used to train on state-of-the-art algorithms such as I3D, R(2+1)D, SlowFast, TSN, and TSM. Finally, an embedded automotive solution was used to demonstrate that both methods are running in real-time. |
| first_indexed | 2024-03-11T01:56:53Z |
| format | Article |
| id | doaj.art-478e93e64da64f0aafd79648981a622d |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T01:56:53Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-478e93e64da64f0aafd79648981a622d2023-11-18T12:33:32ZengMDPI AGSensors1424-82202023-06-012312561010.3390/s23125610Fusion Object Detection and Action Recognition to Predict Violent ActionNelson R. P. Rodrigues0Nuno M. C. da Costa1César Melo2Ali Abbasi3Jaime C. Fonseca4Paulo Cardoso5João Borges6Engineering School, University of Minho, 4800-058 Guimarães, PortugalAlgoritmi Center, University of Minho, 4800-058 Guimarães, PortugalAlgoritmi Center, University of Minho, 4800-058 Guimarães, PortugalAlgoritmi Center, University of Minho, 4800-058 Guimarães, PortugalAlgoritmi Center, University of Minho, 4800-058 Guimarães, PortugalAlgoritmi Center, University of Minho, 4800-058 Guimarães, PortugalAlgoritmi Center, University of Minho, 4800-058 Guimarães, PortugalIn the context of Shared Autonomous Vehicles, the need to monitor the environment inside the car will be crucial. This article focuses on the application of deep learning algorithms to present a fusion monitoring solution which was three different algorithms: a violent action detection system, which recognizes violent behaviors between passengers, a violent object detection system, and a lost items detection system. Public datasets were used for object detection algorithms (COCO and TAO) to train state-of-the-art algorithms such as YOLOv5. For violent action detection, the MoLa InCar dataset was used to train on state-of-the-art algorithms such as I3D, R(2+1)D, SlowFast, TSN, and TSM. Finally, an embedded automotive solution was used to demonstrate that both methods are running in real-time.https://www.mdpi.com/1424-8220/23/12/5610machine learningvisual intelligenceobject detectionimage processingaction recognitionautonomous vehicles |
| spellingShingle | Nelson R. P. Rodrigues Nuno M. C. da Costa César Melo Ali Abbasi Jaime C. Fonseca Paulo Cardoso João Borges Fusion Object Detection and Action Recognition to Predict Violent Action Sensors machine learning visual intelligence object detection image processing action recognition autonomous vehicles |
| title | Fusion Object Detection and Action Recognition to Predict Violent Action |
| title_full | Fusion Object Detection and Action Recognition to Predict Violent Action |
| title_fullStr | Fusion Object Detection and Action Recognition to Predict Violent Action |
| title_full_unstemmed | Fusion Object Detection and Action Recognition to Predict Violent Action |
| title_short | Fusion Object Detection and Action Recognition to Predict Violent Action |
| title_sort | fusion object detection and action recognition to predict violent action |
| topic | machine learning visual intelligence object detection image processing action recognition autonomous vehicles |
| url | https://www.mdpi.com/1424-8220/23/12/5610 |
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