Name
Abstract | ||
|---|---|---|
Counting people is a growing field of interest for researchers in recent years. In-vehicle passenger counting is an interesting problem in this domain that has several applications including High Occupancy Vehicle (HOV) lanes. In this paper, present a new in-vehicle thermal image dataset. We propose a tiny convolutional model to count on-board passengers and compare it to well known methods. We show that our model surpasses state-of-the-art methods in classification and has comparable performance in detection. Moreover, our model outperforms the state-of-the-art architectures in terms ofspeed, making it suitable for deployment on embedded platforms. We present the results of multiple deep learning models and thoroughly analyze them. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/CVPRW.2019.00124 | IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops |
Field | DocType | ISSN |
Computer vision,Thermal,Pattern recognition,Computer science,Occupancy,Artificial intelligence | Conference | 2160-7508 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Farzan Erlik Nowruzi | 1 | 3 | 2.42 |
| Wassim A. El Ahmar | 2 | 0 | 0.34 |
| Robert Laganiere | 3 | 354 | 22.11 |
| Amir H. Ghods | 4 | 0 | 0.34 |