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chanwutk authored Aug 9, 2023
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29 changes: 29 additions & 0 deletions .github/workflows/gh-pages.yml
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name: Publish GitHub Pages

on:
push:
branches: [ main ]

permissions:
contents: write

jobs:
publish:
name: Publish GitHub Pages
runs-on: ubuntu-latest

steps:
- name: Set up Git repository
uses: actions/checkout@v3

- name: Setup GitHub Pages Folder
run: |
rm -rf ./build
mkdir ./build
cp ./README.md ./build/
- name: Publish Website
uses: JamesIves/github-pages-deploy-action@v4
with:
folder: 'build'
single-commit: true
44 changes: 27 additions & 17 deletions README.md
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alt="Github Actions Type Check Status"
src="https://img.shields.io/github/actions/workflow/status/apperception-db/spatialyze/lint.yml?label=Lint&style=for-the-badge"
></a>
<br/>
<a href="https://codecov.io/gh/apperception-db/spatialyze"><img
alt="Codecov Coverage Status"
src="https://img.shields.io/codecov/c/github/apperception-db/spatialyze.svg?label=Coverage&style=for-the-badge"
Expand All @@ -20,27 +21,24 @@
alt="Github Actions Type Check Status"
src="https://img.shields.io/badge/black-000000.svg?label=Code%20style&style=for-the-badge"
></a>
<a href="https://arxiv.org/abs/2308.03276"><img
alt="Github Actions Type Check Status"
src="https://img.shields.io/badge/2308.03276-b31b1b.svg?label=arXiv&style=for-the-badge"
></a>
</p>
## Absract
Videos that are shot using commodity hardware such as phones
and surveillance cameras record various metadata such as time and
location. We encounter such geospatial videos on a daily basis and
such videos have been growing in volume significantly. Yet, we
do not have data management systems that allow users to interact
with such data effectively.
Videos that are shot using commodity hardware such as phones and surveillance cameras record various metadata such as time and location.
We encounter such geospatial videos on a daily basis and such videos have been growing in volume significantly.
Yet, we do not have data management systems that allow users to interact with such data effectively.

In this paper, we describe Spatialyze, a new framework for end-
to-end querying of geospatial videos. Spatialyze comes with a
domain-specific language where users can construct geospatial
video analytic workflows using a 3-step, declarative, build-filter-
observe paradigm. Internally, Spatialyze leverages the declarative
nature of such workflows, the temporal-spatial metadata stored
with videos, and physical behavior of real-world objects to optimize
the execution of workflows. Our results using real-world videos
and workflows show that Spatialyze can reduce execution time by
up to 5.3$`\times`$, while maintaining up to 97.1% accuracy compared to
unoptimized execution.
In this paper, we describe Spatialyze, a new framework for end-to-end querying of geospatial videos.
Spatialyze comes with a domain-specific language where users can construct geospatial video analytic workflows using a 3-step,
declarative, build-filter-observe paradigm.
Internally, Spatialyze leverages the declarative nature of such workflows,
the temporal-spatial metadata stored with videos, and physical behavior of real-world objects to optimize the execution of workflows.
Our results using real-world videos and workflows show that Spatialyze can reduce execution time by up to 5.3x,
while maintaining up to 97.1% accuracy compared to unoptimized execution.

## Requirement
```
Expand Down Expand Up @@ -110,3 +108,15 @@ jupyter-lab
```

The demo notebook first constructs the world. Then it queries for the trajectory of the cars that appeared once in an area of interests within some time interval.

## Citing Spatialyze
```bib
@misc{kittivorawong2023spatialyze,
title={Spatialyze: A Geospatial Video Analytics System with Spatial-Aware Optimizations},
author={Chanwut Kittivorawong and Yongming Ge and Yousef Helal and Alvin Cheung},
year={2023},
eprint={2308.03276},
archivePrefix={arXiv},
primaryClass={cs.DB}
}
```

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