Human detection in near-infrared spectrum
Fast growing human detection technology has been widely applied in different industries. There is a potential for using near-infrared spectrum to perform the detection task. This dissertation is to study the performance of existing human detection algorithms working in near-infrared spectru...
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
2015
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| Online Access: | http://hdl.handle.net/10356/65109 |
| _version_ | 1826109550600650752 |
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| author | Zhao, Ran |
| author2 | Chan Kap Luk |
| author_facet | Chan Kap Luk Zhao, Ran |
| author_sort | Zhao, Ran |
| collection | NTU |
| description | Fast growing human detection technology has been widely applied in different
industries. There is a potential for using near-infrared spectrum to perform the
detection task. This dissertation is to study the performance of existing human
detection algorithms working in near-infrared spectrum.
The human detection task can be accomplished by these two types of detection
methods: full body detection and face detection. Several well-known algorithms
for detecting full bodies and faces are evaluated based on dataset collected in
daytime and nighttime. In daytime, both images in visible spectrum and
near-infrared spectrum are collected while in nighttime only near-infrared images
are collected. The evaluation of these detection methods involves comparisons of
different methods in different spectrums at different time. The comparison results
show the potential of using near-infrared spectrum to detect humans.
A tool for ground truth annotation is implemented to reduce the workload of the
evaluation process. A novel algorithm for bounding rectangle grouping is also
implemented to support the detection experiments. |
| first_indexed | 2024-10-01T02:20:04Z |
| format | Thesis |
| id | ntu-10356/65109 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:20:04Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | ntu-10356/651092023-07-04T16:04:18Z Human detection in near-infrared spectrum Zhao, Ran Chan Kap Luk School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Fast growing human detection technology has been widely applied in different industries. There is a potential for using near-infrared spectrum to perform the detection task. This dissertation is to study the performance of existing human detection algorithms working in near-infrared spectrum. The human detection task can be accomplished by these two types of detection methods: full body detection and face detection. Several well-known algorithms for detecting full bodies and faces are evaluated based on dataset collected in daytime and nighttime. In daytime, both images in visible spectrum and near-infrared spectrum are collected while in nighttime only near-infrared images are collected. The evaluation of these detection methods involves comparisons of different methods in different spectrums at different time. The comparison results show the potential of using near-infrared spectrum to detect humans. A tool for ground truth annotation is implemented to reduce the workload of the evaluation process. A novel algorithm for bounding rectangle grouping is also implemented to support the detection experiments. Master of Science (Signal Processing) 2015-06-15T02:23:35Z 2015-06-15T02:23:35Z 2014 2014 Thesis http://hdl.handle.net/10356/65109 en 61 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Zhao, Ran Human detection in near-infrared spectrum |
| title | Human detection in near-infrared spectrum |
| title_full | Human detection in near-infrared spectrum |
| title_fullStr | Human detection in near-infrared spectrum |
| title_full_unstemmed | Human detection in near-infrared spectrum |
| title_short | Human detection in near-infrared spectrum |
| title_sort | human detection in near infrared spectrum |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing |
| url | http://hdl.handle.net/10356/65109 |
| work_keys_str_mv | AT zhaoran humandetectioninnearinfraredspectrum |