# Source code repository for the paper "Partial 3D Object Retrieval using Local Binary QUICCI Descriptors and Dissimilarity Tree Indexing"

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### Notice: This repository is for archival and reproduction purposes only. 
### Please refer to the following repositories for updated code and documentation:

[libShapeDescriptor](https://github.com/bartvbl/libShapeDescriptor)



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This repository contains:

- A reference implementation of the Dissimilarity Tree proposed in the paper.
- A reference implementation of the Modified Quick Intersection Count Change Image for partial object retrieval purposes.
- A script which can be used to completely reproduce all results presented in the paper.

## Errata

The paper as published contains one oversight, which we would like to correct here. We would like to thank Gustavo Ortiz for making us aware of it.

The following code in Listing 1:

    for bitIndex in bitOrder:
        for descriptor in similarDescriptors:
            if descriptor[bitIndex] == 1:
                similarDescriptors.remove(descriptor)
                dissimilarDescriptors.insert(descriptor)

Should be replaced with:

    for bitIndex in bitOrder:
        if len(dissimilarDescriptors) >= len(similarDescriptors):
            break
        for descriptor in similarDescriptors:
            if descriptor[bitIndex] == 1:
                similarDescriptors.remove(descriptor)
                dissimilarDescriptors.insert(descriptor)



## Instructions

You only need to have python 3 installed, which comes with Ubuntu. Any dependencies needed by the project itself can be installed using the menu system in the script itself.

You can run the script by executing:

```bash
python3 replicate.py
```

From the root of the repository.

Should the script fail due to missing dependencies, you can find shell scripts installing all necessary packages in the scripts/ directory.

Refer to the included Manual PDF for further instructions.

## System Requirements

The RAM and Disk space requirements are only valid when attempting to reproduce the presented results.

The codebase _should_ be able to compile on Windows, but due to some CUDA driver/SDK compatbility issues we have not yet been able to verify this.

Type | Requirements
-----|----------------------------------------------------------------------------
CPU  | Does not matter
RAM  | At least 64GB
Disk | Must have about ~120GB of storage available to store the downloaded datasets
GPU  | Any NVIDIA GPU (project uses CUDA)
OS   | Ubuntu 16 or higher. Project has been tested on 18 and 20.

## Credits

- Development and implementation: Bart Iver van Blokland, [NTNU Visual Computing Lab](https://www.idi.ntnu.no/grupper/vis/)
- Supervision: Theoharis Theoharis, [NTNU Visual Computing Lab](https://www.idi.ntnu.no/grupper/vis/)

If you use (parts of) this project in your research, we kindly ask you reference the papers on which this project is based:

    @article{van2021dissimilarity,
      title={Partial 3D Object Retrieval using Local Binary QUICCI Descriptors and Dissimilarity Tree Indexing},
      author={van Blokland, Bart Iver and Theoharis, Theoharis},
      journal={Computers \& Graphics},
      volume="100",
      pages="32--42",
      year={2021},
      publisher={Elsevier}
    }
    
    @article{van2020indexing,
      title={An Indexing Scheme and Descriptor for 3D Object Retrieval Based on Local Shape Querying},
      author={van Blokland, Bart Iver and Theoharis, Theoharis},
      journal={Computers \& Graphics},
	  volume="92",
	  pages="55--66",
      year={2020},
      publisher={Elsevier}
    }