CIP doi added

Author: christina-shin

_bibliography/people/christina.bib

@@ -9,23 +9,23 @@ @inproceedings{recap
 number={},
 pages={},
 year={2024},
-publisher={ACMMobiCom},
+publisher={ACM},
 abstract={}
 }
 
 @inproceedings{cip,
-doi = {},
-url = {https://www.researchgate.net/publication/381402352_Cooperative_Infrastructure_Perception},
+doi = {10.1109/IoTDI61053.2024.00010},
+url = {https://doi.ieeecomputersociety.org/10.1109/IoTDI61053.2024.00010},
 title = {Cooperative Infrastructure Perception},
 author={Fawad Ahmad and Christina Shin and Weiwu Pang and Branden Leong and Pradipta Ghosh and Ramesh Govindan},
 booktitle={ACM/IEEE Conference on Internet of Things Design and Implementation},
 abbr={IoTDI},
 volume={},
 number={},
-pages={},
+pages={61--72},
 year={2024},
 publisher={ACM/IEEE},
-abstract={}
+abstract={Recent works have considered two qualitatively different approaches to overcome line-of-sight limitations of 3D sensors used for perception: cooperative perception and infrastructure-augmented perception. In this paper, motivated by increasing deployments of infrastructure LiDARs, we explore a third approach – cooperative infrastructure perception. This approach generates perception outputs by fusing outputs of multiple infrastructure sensors, but, to be useful, must do so quickly and accurately. We describe the design, implementation and evaluation of Cooperative Infrastructure Perception (CIP), which uses a combination of novel algorithms and systems optimizations. It produces perception outputs within 100 ms using modest computing resources and with accuracy comparable to the state-of-the-art. CIP, when used to augment vehicle perception, can improve safety. When used in conjunction with offloaded planning, CIP can increase traffic throughput at intersections.}
 }
 
 @inproceedings{aerotraj,