Pedestrian detection is one of the most researched areas in computer vision and is rapidly gaining importance with the emergence of autonomous vehicles and steering assistance technology. Much work has been done in this field, ranging from the collection of extensive datasets to benchmarking of new technologies, but all the research depends on high-quality hardware such as high-resolution cameras, Light Detection and Ranging (LIDAR) and radar.
For detection in low-quality moving camera videos, we use image deblurring techniques to reconstruct image frames and use existing pedestrian detection algorithms and compare our results with the leading research done in this area.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-7711 |
| Date | 25 October 2016 |
| Creators | Hinduja, Saurabh |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
| Rights | default |
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