|
--- |
|
license: cc-by-nc-nd-4.0 |
|
task_categories: |
|
- object-detection |
|
- depth-estimation |
|
- image-classification |
|
language: |
|
- en |
|
size_categories: |
|
- 1K<n<10K |
|
--- |
|
NITCAD (National Institute of Technology Calicut Autonomous Driving) is an effort to collect and label dataset to develop and contribute to autonomous driving efforts in India. |
|
|
|
India has some unique road scenarios such as |
|
- No lanes |
|
- New common objects on roads (like cows, autos, rickshaws) |
|
- No clear traffic signs for pedestrains, zebra crossings etc; |
|
|
|
So, that calls for specialized datasets to train and develop ML models for Indian roads. As a contribution, we have collected stereo and image datasets on Indian roads and labeled different classes that can be used to train Deep Learning models. |
|
|
|
To access the dataset, please fill out the Google Form - https://docs.google.com/forms/d/e/1FAIpQLScv2QXTYy3jwiAlqC9ro-lR_4UhUaWtBDNYQ4jWLZ3eUv3nSA/viewform?usp=sf_link |
|
|
|
For any questions regarding dataset/paper, feel free to email - [email protected], [email protected] with mail subject as “NITCAD Dataset — Doubts” |
|
|
|
**Additional Links:** |
|
1. Medium blog post explaining more details on dataset collection, statistics - https://namburisrinath.medium.com/nitcad-an-object-detection-classification-and-stereo-vision-dataset-for-autonomous-navigation-f28d3fe5b7d9 |
|
2. Github repo - https://github.com/NamburiSrinath/NITCAD-dataset |
|
|
|
If this work helps in your research, please consider to cite as |
|
|
|
@article{srinath2020nitcad, |
|
title={NITCAD-Developing an object detection, classification and stereo vision dataset for autonomous navigation in Indian roads}, |
|
author={Srinath, Namburi GNVV Satya Sai and Joseph, Athul Zac and Umamaheswaran, S and Priyanka, Ch Lakshmi and Nair, Malavika and Sankaran, Praveen}, |
|
journal={Procedia Computer Science}, |
|
volume={171}, |
|
pages={207--216}, |
|
year={2020}, |
|
publisher={Elsevier} |
|
} |
|
|
|
Also you can refer to [Speed estimation using Stereo Vision images](https://ieeexplore.ieee.org/abstract/document/9031876?casa_token=qeCiQNa9m50AAAAA:lOe4ogBfc866e3gPs2s6yesqeHqJ22WElxCQxdl_luLtbeTrgb_eluUFsmMrr8040A_S8U1Lof4y) for the speed estimation by using SIFT (Scale Invariant Feature Transform), YOLO and MC-CNN. |
|
|
|
If this work helps in your research, please consider to cite as |
|
|
|
@inproceedings{umamaheswaran2019stereo, |
|
title={Stereo Vision Based Speed Estimation for Autonomous Driving}, |
|
author={Umamaheswaran, S and Nair, Malavika and Joseph, Athul Zac and Srinath, Namburi GNVV Satya Sai and Priyanka, Ch Lakshmi and Sankaran, Praveen}, |
|
booktitle={2019 International Conference on Information Technology (ICIT)}, |
|
pages={201--205}, |
|
year={2019}, |
|
organization={IEEE} |
|
} |
|
|
|
|
|
**Note:** This project was done in 2019. This dataset card is mainly created to improve visibility, searchability for the datasets via the Huggingface community. |
