A new pattern recognition method for abnormal event detection in crowded scenarios
Cataloged from PDF version of thesis report.
| Egile nagusia: | |
|---|---|
| Beste egile batzuk: | |
| Formatua: | Thesis |
| Hizkuntza: | English |
| Argitaratua: |
BRAC University
2017
|
| Gaiak: | |
| Sarrera elektronikoa: | http://hdl.handle.net/10361/8241 |
| id |
10361-8241 |
|---|---|
| record_format |
dspace |
| spelling |
10361-82412022-01-26T10:08:17Z A new pattern recognition method for abnormal event detection in crowded scenarios Mostafa, Tahjid Ashfaque Ali, Md. Haider Uddin, Jia Department of Computer Science and Engineering, BRAC University Image processing Pattern recognition Cataloged from PDF version of thesis report. Includes bibliographical references (page 31-34). This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. We propose an autonomous video surveillance system which analyzes surveillance footages of extremely crowded scenes and detects abnormal events. For any particular scenario, any event that diverts from the usual pattern can be classified as an abnormal event. The model analyzes the local spatial-temporal motion pattern and detects abnormal motion variations and sudden changes. It can be divided into two major parts, selecting a set of Points of Interest (POI) from given frames using ORB (Oriented FAST and Rotated BRIEF) feature detector and tracking them across multiple frames and dividing the input video frame in a number of cubes and track the motion patterns in each of the cubes for spatial-temporal statistical deviations. To evaluate the performance of proposed model we utilize several datasets and compare the acquired results of the proposed model with various state-of-the art models. Experimental results demonstrate that the proposed model outperforms the other models by exhibiting an average of 96.12% accuracy using Convolutional Neural Network. Tahjid Ashfaque Mostafa B. Computer Science and Engineering 2017-06-14T04:26:26Z 2017-06-14T04:26:26Z 2017 4/18/2017 Thesis ID 13101098 http://hdl.handle.net/10361/8241 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 34 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Image processing Pattern recognition |
| spellingShingle |
Image processing Pattern recognition Mostafa, Tahjid Ashfaque A new pattern recognition method for abnormal event detection in crowded scenarios |
| description |
Cataloged from PDF version of thesis report. |
| author2 |
Ali, Md. Haider |
| author_facet |
Ali, Md. Haider Mostafa, Tahjid Ashfaque |
| format |
Thesis |
| author |
Mostafa, Tahjid Ashfaque |
| author_sort |
Mostafa, Tahjid Ashfaque |
| title |
A new pattern recognition method for abnormal event detection in crowded scenarios |
| title_short |
A new pattern recognition method for abnormal event detection in crowded scenarios |
| title_full |
A new pattern recognition method for abnormal event detection in crowded scenarios |
| title_fullStr |
A new pattern recognition method for abnormal event detection in crowded scenarios |
| title_full_unstemmed |
A new pattern recognition method for abnormal event detection in crowded scenarios |
| title_sort |
new pattern recognition method for abnormal event detection in crowded scenarios |
| publisher |
BRAC University |
| publishDate |
2017 |
| url |
http://hdl.handle.net/10361/8241 |
| work_keys_str_mv |
AT mostafatahjidashfaque anewpatternrecognitionmethodforabnormaleventdetectionincrowdedscenarios AT mostafatahjidashfaque newpatternrecognitionmethodforabnormaleventdetectionincrowdedscenarios |
| _version_ |
1814307328758906880 |