360° tracking using a virtual PTZ camera
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 10484 LNCS, Page: 62-72
2017
- 3Citations
- 3Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
Object tracking using still or PTZ cameras is a hard task for large spaces and needs several devices to completely cover the area or to track multiple subjects. The introduction of 360° camera technology offers a complete view of the scene in a single image and can be useful to reduce the number of devices needed in the tracking problem. In this paper we present a framework using 360° cameras to simulate an unlimited number of PTZ cameras and to be used for tracking. The proposed method to track a single target process an equirectangular view of the scene and obtains a model of the moving object in the image plane. The target is tracked analyzing the next frame of the video sequence and estimating the P,T and Z shifts needed to keep the target in the center of the virtual camera view. The framework allows to use a single 360° device to obtain an equirectangular video sequence and to apply the proposed tracking strategy on each target simulating several virtual PTZ cameras.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85032479195&origin=inward; http://dx.doi.org/10.1007/978-3-319-68560-1_6; https://link.springer.com/10.1007/978-3-319-68560-1_6; https://dx.doi.org/10.1007/978-3-319-68560-1_6; https://link.springer.com/chapter/10.1007/978-3-319-68560-1_6
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know