Very naive implementation of Multi-object tracking in Rust programming language

Table of Contents

• About
• How to use
• References

About

Why is it even exists when there are a lot of other solutions (better perfomance, better logic, better overall and etc.)?

It is simple as that:

What I cannot create, I do not understand Richard Feynman

What is this good for?

You can use this library to track vehicles / peoples and etc. when you don't need that much accuracy or ReID.

What Multi-Object tracking algorithms are implemented?

• Centroids distance + diagonal - src/mot/simple.rs#L56
• IoU - src/mot/iou_tracker.rs#L58
• ByteTrack using greedy matching algorithm - src/mot/bytetrack.rs#L260
• ByteTrack using Hungarian algorithm via pathfinding crate - src/mot/bytetrack.rs#L233

Are more advanced algorithms considered to be implemented in futher?

Yes, I do think so. I guess that SORT will be the next one.

If you want to you can contribute via opening Pull Request

Some examples

Simple centroid IoU tracker for three simple tracks	ByteTrack + Hungarian algorithm for three simple tracks

Simple centroid IoU tracker for spread tracks	ByteTrack + Hungarian algorithm for spread tracks

How to use

Add dependency to your Cargo.toml file

[package]
....

[dependencies]
...
mot-rs = "0.2.0"
...

Let's create really synthetic example and define similar trajectories for three objects. We're using pretty simple MOT algorithm, so no hard tasks for now. We are going to use itertools just to simplify zipping trajectories.

use mot_rs::mot::{
    SimpleTracker,
    SimpleBlob
};
use mot_rs::utils::{
    Rect
};

fn main() {
    let bboxes_one: Vec<Vec<f32>> = vec![vec![236, -25, 386, 35], vec![237, -24, 387, 36], vec![238, -22, 388, 38], vec![236, -20, 386, 40], vec![236, -19, 386, 41], vec![237, -18, 387, 42], vec![237, -18, 387, 42], vec![238, -17, 388, 43], vec![237, -14, 387, 46], vec![237, -14, 387, 46], vec![237, -12, 387, 48], vec![237, -12, 387, 48], vec![237, -11, 387, 49], vec![237, -11, 387, 49], vec![237, -10, 387, 50], vec![237, -10, 387, 50], vec![237, -8, 387, 52], vec![237, -8, 387, 52], vec![236, -7, 386, 53], vec![236, -7, 386, 53], vec![236, -6, 386, 54], vec![236, -6, 386, 54], vec![236, -2, 386, 58], vec![235, 0, 385, 60], vec![236, 2, 386, 62], vec![236, 5, 386, 65], vec![236, 9, 386, 69], vec![235, 12, 385, 72], vec![235, 14, 385, 74], vec![233, 16, 383, 76], vec![232, 26, 382, 86], vec![233, 28, 383, 88], vec![233, 40, 383, 100], vec![233, 30, 383, 90], vec![232, 22, 382, 82], vec![232, 34, 382, 94], vec![232, 21, 382, 81], vec![233, 40, 383, 100], vec![232, 40, 382, 100], vec![232, 40, 382, 100], vec![232, 36, 382, 96], vec![232, 53, 382, 113], vec![232, 50, 382, 110], vec![233, 55, 383, 115], vec![232, 50, 382, 110], vec![234, 68, 384, 128], vec![231, 49, 381, 109], vec![232, 68, 382, 128], vec![231, 31, 381, 91], vec![232, 64, 382, 124], vec![233, 71, 383, 131], vec![231, 64, 381, 124], vec![231, 74, 381, 134], vec![231, 64, 381, 124], vec![230, 77, 380, 137], vec![232, 82, 382, 142], vec![232, 78, 382, 138], vec![232, 78, 382, 138], vec![231, 79, 381, 139], vec![231, 79, 381, 139], vec![231, 91, 381, 151], vec![232, 78, 382, 138], vec![232, 78, 382, 138], vec![233, 90, 383, 150], vec![232, 92, 382, 152], vec![232, 92, 382, 152], vec![233, 98, 383, 158], vec![232, 100, 382, 160], vec![231, 92, 381, 152], vec![233, 110, 383, 170], vec![234, 92, 384, 152], vec![234, 92, 384, 152], vec![234, 110, 384, 170], vec![234, 92, 384, 152], vec![233, 104, 383, 164], vec![234, 111, 384, 171], vec![234, 106, 384, 166], vec![234, 106, 384, 166], vec![233, 124, 383, 184], vec![236, 125, 386, 185], vec![236, 125, 386, 185], vec![232, 120, 382, 180], vec![236, 131, 386, 191], vec![232, 132, 382, 192], vec![238, 139, 388, 199], vec![236, 141, 386, 201], vec![232, 151, 382, 211], vec![236, 145, 386, 205], vec![236, 145, 386, 205], vec![231, 133, 381, 193], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208], vec![237, 148, 387, 208]];
    let bboxes_two: Vec<Vec<f32>> = vec![vec![321, -25, 471, 35], vec![322, -24, 472, 36], vec![323, -22, 473, 38], vec![321, -20, 471, 40], vec![321, -19, 471, 41], vec![322, -18, 472, 42], vec![322, -18, 472, 42], vec![323, -17, 473, 43], vec![322, -14, 472, 46], vec![322, -14, 472, 46], vec![322, -12, 472, 48], vec![322, -12, 472, 48], vec![322, -11, 472, 49], vec![322, -11, 472, 49], vec![322, -10, 472, 50], vec![322, -10, 472, 50], vec![322, -8, 472, 52], vec![322, -8, 472, 52], vec![321, -7, 471, 53], vec![321, -7, 471, 53], vec![321, -6, 471, 54], vec![321, -6, 471, 54], vec![321, -2, 471, 58], vec![320, 0, 470, 60], vec![321, 2, 471, 62], vec![321, 5, 471, 65], vec![321, 9, 471, 69], vec![320, 12, 470, 72], vec![320, 14, 470, 74], vec![318, 16, 468, 76], vec![317, 26, 467, 86], vec![318, 28, 468, 88], vec![318, 40, 468, 100], vec![318, 30, 468, 90], vec![317, 22, 467, 82], vec![317, 34, 467, 94], vec![317, 21, 467, 81], vec![318, 40, 468, 100], vec![317, 40, 467, 100], vec![317, 40, 467, 100], vec![317, 36, 467, 96], vec![317, 53, 467, 113], vec![317, 50, 467, 110], vec![318, 55, 468, 115], vec![317, 50, 467, 110], vec![319, 68, 469, 128], vec![316, 49, 466, 109], vec![317, 68, 467, 128], vec![316, 31, 466, 91], vec![317, 64, 467, 124], vec![318, 71, 468, 131], vec![316, 64, 466, 124], vec![316, 74, 466, 134], vec![316, 64, 466, 124], vec![315, 77, 465, 137], vec![317, 82, 467, 142], vec![317, 78, 467, 138], vec![317, 78, 467, 138], vec![316, 79, 466, 139], vec![316, 79, 466, 139], vec![316, 91, 466, 151], vec![317, 78, 467, 138], vec![317, 78, 467, 138], vec![318, 90, 468, 150], vec![317, 92, 467, 152], vec![317, 92, 467, 152], vec![318, 98, 468, 158], vec![317, 100, 467, 160], vec![316, 92, 466, 152], vec![318, 110, 468, 170], vec![319, 92, 469, 152], vec![319, 92, 469, 152], vec![319, 110, 469, 170], vec![319, 92, 469, 152], vec![318, 104, 468, 164], vec![319, 111, 469, 171], vec![319, 106, 469, 166], vec![319, 106, 469, 166], vec![318, 124, 468, 184], vec![321, 125, 471, 185], vec![321, 125, 471, 185], vec![317, 120, 467, 180], vec![321, 131, 471, 191], vec![317, 132, 467, 192], vec![323, 139, 473, 199], vec![321, 141, 471, 201], vec![317, 151, 467, 211], vec![321, 145, 471, 205], vec![321, 145, 471, 205], vec![316, 133, 466, 193], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208], vec![322, 148, 472, 208]];
    let bboxes_three: Vec<Vec<f32>> = vec![vec![151, -25, 301, 35], vec![152, -24, 302, 36], vec![153, -22, 303, 38], vec![151, -20, 301, 40], vec![151, -19, 301, 41], vec![152, -18, 302, 42], vec![152, -18, 302, 42], vec![153, -17, 303, 43], vec![152, -14, 302, 46], vec![152, -14, 302, 46], vec![152, -12, 302, 48], vec![152, -12, 302, 48], vec![152, -11, 302, 49], vec![152, -11, 302, 49], vec![152, -10, 302, 50], vec![152, -10, 302, 50], vec![152, -8, 302, 52], vec![152, -8, 302, 52], vec![151, -7, 301, 53], vec![151, -7, 301, 53], vec![151, -6, 301, 54], vec![151, -6, 301, 54], vec![151, -2, 301, 58], vec![150, 0, 300, 60], vec![151, 2, 301, 62], vec![151, 5, 301, 65], vec![151, 9, 301, 69], vec![150, 12, 300, 72], vec![150, 14, 300, 74], vec![148, 16, 298, 76], vec![147, 26, 297, 86], vec![148, 28, 298, 88], vec![148, 40, 298, 100], vec![148, 30, 298, 90], vec![147, 22, 297, 82], vec![147, 34, 297, 94], vec![147, 21, 297, 81], vec![148, 40, 298, 100], vec![147, 40, 297, 100], vec![147, 40, 297, 100], vec![147, 36, 297, 96], vec![147, 53, 297, 113], vec![147, 50, 297, 110], vec![148, 55, 298, 115], vec![147, 50, 297, 110], vec![149, 68, 299, 128], vec![146, 49, 296, 109], vec![147, 68, 297, 128], vec![146, 31, 296, 91], vec![147, 64, 297, 124], vec![148, 71, 298, 131], vec![146, 64, 296, 124], vec![146, 74, 296, 134], vec![146, 64, 296, 124], vec![145, 77, 295, 137], vec![147, 82, 297, 142], vec![147, 78, 297, 138], vec![147, 78, 297, 138], vec![146, 79, 296, 139], vec![146, 79, 296, 139], vec![146, 91, 296, 151], vec![147, 78, 297, 138], vec![147, 78, 297, 138], vec![148, 90, 298, 150], vec![147, 92, 297, 152], vec![147, 92, 297, 152], vec![148, 98, 298, 158], vec![147, 100, 297, 160], vec![146, 92, 296, 152], vec![148, 110, 298, 170], vec![149, 92, 299, 152], vec![149, 92, 299, 152], vec![149, 110, 299, 170], vec![149, 92, 299, 152], vec![148, 104, 298, 164], vec![149, 111, 299, 171], vec![149, 106, 299, 166], vec![149, 106, 299, 166], vec![148, 124, 298, 184], vec![151, 125, 301, 185], vec![151, 125, 301, 185], vec![147, 120, 297, 180], vec![151, 131, 301, 191], vec![147, 132, 297, 192], vec![153, 139, 303, 199], vec![151, 141, 301, 201], vec![147, 151, 297, 211], vec![151, 145, 301, 205], vec![151, 145, 301, 205], vec![146, 133, 296, 193], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208], vec![152, 148, 302, 208]];
    let mut mot = SimpleTracker::new(5, 15.0);
    let dt = 1.0/25.00; // emulate 25 fps

    for (bbox_one, bbox_two, bbox_three) in itertools::izip!(bboxes_one, bboxes_two, bboxes_three) {
        let blob_one = SimpleBlob::new_with_dt(Rect::new(bbox_one[0], bbox_one[1], bbox_one[2]-bbox_one[0], bbox_one[3]-bbox_one[1]), dt);
        let blob_two = SimpleBlob::new_with_dt(Rect::new(bbox_two[0],bbox_two[1],bbox_two[2] -bbox_two[0],bbox_two[3]- bbox_two[1]), dt);
        let blob_three = SimpleBlob::new_with_dt(Rect::new(bbox_three[0],bbox_three[1],bbox_three[2] -bbox_three[0],bbox_three[3]- bbox_three[1]), dt);

        match mot.match_objects(vec![blob_one, blob_two, blob_three]) {
            Ok(_) => {},
            Err(err) => {
                println!("{:?}", err);
            }
        };

        println!("id;track");
        for object in &mot.objects {
            print!("{};", object.0);
            let track = object.1.get_track();
            for (idx, pt) in track.iter().enumerate() {
                if idx == track.len() - 1 {
                    print!("{},{}", pt.x, pt.y);
                } else {
                    print!("{},{}|", pt.x, pt.y);
                }
            }
            println!();
        }
    }
}

If we plot results on a single image we should get something like:

References

• Implementation of Kalman filter, Dimitrii Lopanov, 2023
• Wikipedia