Evaluation of different techniques for foreground object classification under illumination changes
Recently, a lot of attentions have been paid to the object-based analysis in camera surveillance for shortening the gap between high level image semantics and low level image representations. In the experiments, the main focus was on two-class foreground object classification, car and human categori...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
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2015
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| Online Access: | http://hdl.handle.net/10356/62582 |
| _version_ | 1824456974347010048 |
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| author | Nguyen, Hang Nga |
| author2 | Ho Shen-Shyang |
| author_facet | Ho Shen-Shyang Nguyen, Hang Nga |
| author_sort | Nguyen, Hang Nga |
| collection | NTU |
| description | Recently, a lot of attentions have been paid to the object-based analysis in camera surveillance for shortening the gap between high level image semantics and low level image representations. In the experiments, the main focus was on two-class foreground object classification, car and human categories. The experiments had been intensively tested on four different datasets. Various problems existed in those datasets. These problems included the illumination changes, shading, high variations of interested objects’ appearances which are caused by geometrical transformations such as scale, orientation and affine transformations. A comprehensive comparison of selected methods for foreground detection, feature transformation and classification had been conducted to evaluate their effects on the final classification accuracy. The first comparison was done on two foreground detection methods, the traditional Otsu method and the proposed method called Pixel Analysis. The other comparisons were evaluated for four combinations of two feature transformations (histogram transformation vs. binary transformation) and two classification methods (KNN vs. SVM). The results and discussions showed that the combination of binary transformation and SVM was the best for the two-class foreground object classification. |
| first_indexed | 2025-02-19T04:02:37Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/62582 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T04:02:37Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | ntu-10356/625822023-03-03T20:43:29Z Evaluation of different techniques for foreground object classification under illumination changes Nguyen, Hang Nga Ho Shen-Shyang School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition Recently, a lot of attentions have been paid to the object-based analysis in camera surveillance for shortening the gap between high level image semantics and low level image representations. In the experiments, the main focus was on two-class foreground object classification, car and human categories. The experiments had been intensively tested on four different datasets. Various problems existed in those datasets. These problems included the illumination changes, shading, high variations of interested objects’ appearances which are caused by geometrical transformations such as scale, orientation and affine transformations. A comprehensive comparison of selected methods for foreground detection, feature transformation and classification had been conducted to evaluate their effects on the final classification accuracy. The first comparison was done on two foreground detection methods, the traditional Otsu method and the proposed method called Pixel Analysis. The other comparisons were evaluated for four combinations of two feature transformations (histogram transformation vs. binary transformation) and two classification methods (KNN vs. SVM). The results and discussions showed that the combination of binary transformation and SVM was the best for the two-class foreground object classification. Bachelor of Engineering (Computer Science) 2015-04-21T06:19:50Z 2015-04-21T06:19:50Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/62582 en Nanyang Technological University 51 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition Nguyen, Hang Nga Evaluation of different techniques for foreground object classification under illumination changes |
| title | Evaluation of different techniques for foreground object classification under illumination changes |
| title_full | Evaluation of different techniques for foreground object classification under illumination changes |
| title_fullStr | Evaluation of different techniques for foreground object classification under illumination changes |
| title_full_unstemmed | Evaluation of different techniques for foreground object classification under illumination changes |
| title_short | Evaluation of different techniques for foreground object classification under illumination changes |
| title_sort | evaluation of different techniques for foreground object classification under illumination changes |
| topic | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition |
| url | http://hdl.handle.net/10356/62582 |
| work_keys_str_mv | AT nguyenhangnga evaluationofdifferenttechniquesforforegroundobjectclassificationunderilluminationchanges |