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FINAL PPT ALL.pptx

1. Apr 2023
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FINAL PPT ALL.pptx

  1. 1 AGENDA : PRESENTATION: Abstract Introduction Existing System Proposed System Literature Review Software & Hardware requirements
  2. ABSTRACT • Computer vision-based accident detection through video surveillance has become a beneficial but daunting task. In this project, detection of road accidents is proposed. • The proposed framework capitalizes on axis bounding box technique for accurate object detection followed by an efficient centroid based GMM algorithm for surveillance footage. • The proposed framework provides a robust method to achieve a high Detection Rate and a low False Alarm Rate on general road-traffic CCTV surveillance footage. • This framework was evaluated on diverse conditions such as broad daylight, low visibility, rain, hail, and snow using the proposed dataset. • This framework was found effective and paves the way to the development of general-purpose vehicular accident detection algorithms in real-time. • This project also use geopy library to capture the live location and we can send notification to the nearby police station and hospital with the snap of accident image. • So by seeing the image they can take necessary resource allocation and the recovery is made very easy in less time. Alarm buzzer is also included to notify the nearby people. 2 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
  3. INTRODUCTION • Road-side traffic flow has turned out to be an elementary share of human lifestyles and has an impact on several services and activities on a day-to-day basis. • It can be seen that 1.25 million human beings lose their lives due to vehicular accidents. • Several human casualties occur due to delays in reporting accident cases in a timely fashion causing further delays for receiving medical assistance. • So finding the accident and alerting the nearby hospital play an important role. • Detection of moving objects, is an important research area in computer vision research, which is applied to more and more video surveillance systems. • To obtain the exact outline of the object after the object tracking and processing is very important, affecting the performance of the whole system. Background subtraction method is one of the commonly used methods for moving object detection which helps us to find the moving vehicle. And the angle cordinate intersection helps us to find the accident. 3 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
  4. EXISTING SYSTEM Collision detection based on exceeding the threshold of acceleration using an accelerometer to measure the dynamic force caused by movement and the gravity force. The rollover detection based on exceeding the threshold of the vehicle angle of inclination. Artificial Neural Networks (ANN), Support Vector Machine (SVM), and Random Forests (RF) DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING 4
  5. DISADVANTAGE • The occurrence of an accident and the dispatch of emergency medical services. • Costly, power- consuming and inefficient. • Completely depend on the sensors. • Crash Detection Algorithm DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING 5
  6. 6 OBJECTIVE: • To know the accident by feature extraction from the image and video as input format. • Based on the injury as it normal or in serious condition sending an alert message to nearby hospital. • Using CCTV surveillance detect the accident. • It reduce the late communication timing among hospitals and accident spot.
  7. PROPOSED SYSTEM • GAUSSIAN MIXTURE MODEL – GMM for background subtraction. • Moving vehicle detection and bounding box interaction detection. • Geopy library to capture the live location • Smtp for gmail notification • Send notification to the nearby police station and hospital with the snap of accident image. • So by seeing the image they can take necessary resource allocation and the recovery is made very easy in less time. • Alarm buzzer is also included to notify the nearby people near to cctv camera. DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING 7
  8. GMM Background Sub Feature Extraction - Find Contour Set Threshold Alert Attach Snapshot Alert Hospital/police station Geopy share Location Bounding Box Accident Detection No Yes
  9. DATA FLOW DIAGRAM 9
  10. CONCLUSION • The proposed solution is implemented on python, using the OpenCV bindings. • The traffic camera footages from variety of sources are in implementation. • A simple interface is developed for the user to select the region of interest to be analyzed and then image processing techniques are applied to detect the accident • Currently proposed system works with already captured videos but it can be modified to be used for processing live video streams • One of the limitations of the system is that it is not efficient at detection of occlusion of the vehicles which affects the counting as well as classification. • This problem could be solved by introducing the second level feature classification such as the classification on the bases of color. • Another limitation of the current system is that it needs human supervision for defining the region of interest. The user has to define an imaginary line where centroid of the contours intersects for the counting of vehicles hence the accuracy is dependent on the judgment of the human supervisor. • Furthermore the camera angle also affects the system hence camera calibration techniques could be used for the detection of the lane for the better view of the road and increasing the efficiency. • The system is not capable of detection of vehicles in the night as it needs the foreground objects to be visible for extraction of contour properties as well as features for the classification using SIFT features. 10
  11. REFERENCES • T. Rahman, "Road Accidents in Bangladesh: An Alarming Issue", the World Bank, 2012. [Online]. • K. M. Habibullah, A. Alam, S. Saha, A. Amin and A. K. Das, " A Driver-Centric Carpooling: Optimal RouteFinding Model using Heuristic Multi–Objective Search," 2019 4th International Conference on Computer and Communication Systems (ICCCS), Singapore, 2019. • K. M. Habibullah, A. Alam, S. Saha, A. Amin and A. K. Das, " A Driver-Centric Carpooling: Optimal RouteFinding Model using Heuristic Multi–Objective Search," 2019 4th International Conference on Computer and Communication Systems (ICCCS), Singapore, 2019 • M. S. Satu, S. Ahamed, F. Hossain, T. Akter and D. M. Farid, "Mining traffic accident data of N5 national highway in Bangladesh employing decision trees," 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), Dhaka, 2017, pp. 722-725. • Nicky Kattukkaran, Arun George and T P. Mithun Haridas, Intelligent accident detection and alert system for emergency medical assistance, pp. 1-6, 2017. • Y. Yorozu, M. Hirano, K. Oka and Y. Tagawa, "Electron spectroscopy studies on magneto-optical media and plastic substrate interface", IEEE Transl. J. Magn. Japan, vol. 2, pp. 740-741, August 1987. • S. Santos, Guide to NEO-6M GPS Module Arduino. Random Nerd Tutorials, June 2019, [online] Available: https://randomnerdtutorials.com/guide-to-neo-6m-gps-module-with-arduino/. DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING 11
  12. THANK YOU DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING 12
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