{"id":2042,"date":"2024-01-29T16:29:35","date_gmt":"2024-01-29T19:29:35","guid":{"rendered":"https:\/\/web.inf.ufpr.br\/vri\/?page_id=2042"},"modified":"2024-02-06T10:16:42","modified_gmt":"2024-02-06T13:16:42","slug":"ufpr-planalto801","status":"publish","type":"page","link":"https:\/\/web.inf.ufpr.br\/vri\/databases\/ufpr-planalto801\/","title":{"rendered":"UFPR-Planalto801"},"content":{"rendered":"\n

This dataset, called UFPR-Planalto801, has been introduced in our VISAPP paper\u00a0[PDF]<\/a>\u00a0and contains images of a real-world surveillance scenario and it is mainly intended for use in the development of security systems, specially regarding people tracking and re-identification. It is composed of videos taken from cameras inside the the Pal\u00e1cio do Planalto, in Brazil, during protesters invasion on January 8, 2023. These videos are part of the footage released to the public by the Brazilian Supreme Court, according to the\u00a0GSI Note<\/a>\u00a0released to the press on April 23, 2023. (last access: January 15,2024). The complete footage is available for download through this\u00a0link<\/a>.<\/p>\n\n\n\n

You can find updates on this project at the following link: https:\/\/github.com\/cbacelarufc\/UFPR-Planalto801<\/a><\/p>\n\n\n\n

The UFPR-Planalto801 dataset contains 14 videos of several lengths, with a resolution of 1920×1080 pixels, and encoded to 24 FPS. There are approximately 6 hours of video, with 518,050 frames and 510,471 annotated detections, as presented in the table below. <\/p>\n\n\n\n

The full details and results regarding this dataset are in our paper<\/a>.<\/p>\n\n\n\n

Videos<\/th>Frames<\/th>Duration<\/th>Detections<\/th>Tracks<\/th><\/tr><\/thead>
Video01<\/td>24119<\/td>0:16:44<\/td>7438<\/td>28<\/td><\/tr>
Video02<\/td>6743<\/td>0:04:40<\/td>25686<\/td>79<\/td><\/tr>
Video03<\/td>10811<\/td>0:07:30<\/td>31246<\/td>52<\/td><\/tr>
Video04<\/td>41850<\/td>0:29:03<\/td>42537<\/td>68<\/td><\/tr>
Video05<\/td>42361<\/td>0:29:25<\/td>89531<\/td>95<\/td><\/tr>
Video06<\/td>42857<\/td>0:29:45<\/td>83949<\/td>46<\/td><\/tr>
Video07<\/td>38164<\/td>0:26:30<\/td>33582<\/td>28<\/td><\/tr>
Video08<\/td>34313<\/td>0:23:49<\/td>33191<\/td>19<\/td><\/tr>
Video09<\/td>16997<\/td>0:11:48<\/td>4046<\/td>15<\/td><\/tr>
Video10<\/td>81956<\/td>0:56:54<\/td>104509<\/td>167<\/td><\/tr>
Video11<\/td>78907<\/td>0:54:47<\/td>27686<\/td>80<\/td><\/tr>
Video12<\/td>79464<\/td>0:55:11<\/td>15788<\/td>38<\/td><\/tr>
Video13<\/td>560<\/td>0:00:23<\/td>1025<\/td>2<\/td><\/tr>
Video14<\/td>18948<\/td>0:13:09<\/td>10257<\/td>19<\/td><\/tr>
Total<\/strong><\/td>518050<\/strong><\/td>5:59:38<\/strong><\/td>510471<\/strong><\/td>736<\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Annotations are in MOTChallenge format (https:\/\/motchallenge.net\/<\/a>):<\/p>\n\n\n\n

<frame>,<id>,<left>,<top>,<width>,<height>,<conf>,<x>,<y>,<z><\/code><\/pre>\n\n\n\n
UFPR-PLanalto801\n\u251c\u2500\u2500 all\n\u2502   \u251c\u2500\u2500 VIDEO-01\n\u2502   \u2502   \u2502\u2500\u2500 gt\n\u2502   \u2502   |   \u2514\u2500\u2500 gt.txt\n\u2502   \u2502   \u2502\u2500\u2500 img1\n\u2502   \u2502       \u251c\u2500\u2500 000001.jpg\n\u2502   \u2502       \u251c\u2500\u2500 000002.jpg\n\u2502   \u2502       \u251c\u2500\u2500 000003.jpg\n\u2502   \u2502       \u251c\u2500\u2500 000004.jpg\n...\n\u2502   \u251c\u2500\u2500 VIDEO-02\n\u2502   \u2502   \u2502\u2500\u2500 gt\n\u2502   \u2502   |   \u2514\u2500\u2500 gt.txt\n\u2502   \u2502   \u2502\u2500\u2500 img1\n\u2502   \u2502       \u251c\u2500\u2500 000001.jpg\n\u2502   \u2502       \u251c\u2500\u2500 000002.jpg\n\u2502   \u2502       \u251c\u2500\u2500 000003.jpg\n\u2502   \u2502       \u251c\u2500\u2500 000004.jpg\n...<\/code><\/pre>\n\n\n\n
Here are some frames from the dataset:
<\/a><\/p>\n\n\n\n
Here are some examples of people framing from the dataset:<\/p>\n\n\n\n
\"\"<\/a><\/figure>\n\n\n\n
Here are some examples of tracklets from the dataset:<\/p>\n\n\n\n\n
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<\/a>How to obtain the dataset<\/h2>\n\n\n\n
<\/p>\n\n\n\n
The UFPR-Planalto801 dataset annotations are released for academic research only and is free to researchers from educational or research institutes for non-commercial purposes<\/strong>.<\/p>\n\n\n\n
We extract pieces of a public footage in order to produce the The UFPR-Planalto801 dataset. We annotated the positions of people in frames, since original images have no annotations.<\/p>\n\n\n\n
You can access the complete footage through this  link<\/a>, but before you can download the dataset annotations, we kindly ask you to register by sending an e-mail with the following subject: \u201cUFPR-Planalto801 Dataset\u201d to the first author (cristianobac@ufc.br), so that we can know who is using the provided data and notify you of future updates. Please include your name, affiliation and department in the e-mail. Once you have registered, you will receive a link to download the database. In general, a download link will take 1-3 workdays to issue.<\/p>\n\n\n\n
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<\/a>Citation<\/h2>\n\n\n\n
If you use the UFPR-Planalto801 dataset in your research, please cite our paper:<\/p>\n\n\n\n