Salmon tracking
Data Set (DS) | Alaska Fisheries Science Center (AFSC)GUID: gov.noaa.nmfs.inport:79020 | Updated: March 31, 2026 | Published / External
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Summary
Short Citation
Alaska Fisheries Science Center, 2026: Salmon tracking, https://www.fisheries.noaa.gov/inport/item/79020.
Full Citation Examples
This dataset contains the annotated data and object detection models used to evaluate multi-object tracking (MOT) algorithms for tracking Pacific salmon (Oncorhynchus spp.) in videos collected in a commercial walleye pollock (Gadus chalcogrammus) trawl in Alaska. The annotated data contains track annotations for all Pacific salmon and walleye pollock present and frame level annotations that describe the trawl and background conditions. The annotated data is composed of 11,572 salmon and 73,394 pollock annotations from 16,989 video frames that came from 184 video clips. Five sizes of YOLO12 detection models (n, s, m, l, and x) were fine-tuned and evaluated for pollock and salmon detection and four tracking algorithms (BoT-SORT, ByteTrack, Intersection over Union, and Centroid) were used to assess MOT of bycaught Pacific salmon in trawls. All five YOLO12 models are provided as part of this dataset.
Bycatch reduction devices (BRDs) are used in the Alaska walleye pollock (Gadus chalcogrammus) fishery to reduce Pacific salmon (Oncorhynchus spp.) bycatch. Evaluation of BRD effectiveness often requires people to process collected or live-feed video, which can be a tedious, expensive, and time-consuming task. Deep learning can be used to automate the detection, classification, and tracking of fish in videos to support BRD and other fisheries bycatch work. This dataset was developed to evaluate the performance of widely-available, open-source pre-trained object detection models for the task of pollock and salmon detection and multi-object tracking models for salmon tracking.
Data Access & Downloads
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PNG - Portable Network Graphics Format, <2MB
This folder within the Alaska Fisheries Science Center's Google cloud storage contains the data and object detection models used for the Lurbur et al. 2026 study on multi-object tracking of salmon in trawl videos from the Alaska commercial pollock fishery.
The 'annotated_data' folder contains a folder for each of the 184 video clips used in the study that provides video frames as png files and the annotations as a custom COCO json file.
The 'models' folder contains the object detection models that were used in the study.
The 'documentation' folder contains text files that provide details about the data and the cloud storage file structure.
The 'tow_data' folder contains videos and data relevant to the Wilson et al. 2025 study and is not relevant to the Lurbur et al. 2026 study.
If using these data, please cite https://doi.org/10.1093/icesjms/fsaf168 and/or https://doi.org/[placeholder]
URLs
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Source code for salmon tracking work from Lurbur et al. 2026.
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Dataset that includes annotated data and models for the Lurbur et al. 2026 study.
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Scientific publication
Child Items
No Child Items for this record.
Contact Information
Point of Contact
Katherine Wilson
katherine.wilson@noaa.gov
2065264474
Extents
-166.03722222222° W,
-165.59805555556° E,
54.69833333333° N,
54.32472222222° S
2020-08-07 - 2020-08-10
Item Identification
| Title: | Salmon tracking |
|---|---|
| Creation Date: | 2023-03-08 |
| Revision Date: | 2026-01-20 |
| Abstract: |
This dataset contains the annotated data and object detection models used to evaluate multi-object tracking (MOT) algorithms for tracking Pacific salmon (Oncorhynchus spp.) in videos collected in a commercial walleye pollock (Gadus chalcogrammus) trawl in Alaska. The annotated data contains track annotations for all Pacific salmon and walleye pollock present and frame level annotations that describe the trawl and background conditions. The annotated data is composed of 11,572 salmon and 73,394 pollock annotations from 16,989 video frames that came from 184 video clips. Five sizes of YOLO12 detection models (n, s, m, l, and x) were fine-tuned and evaluated for pollock and salmon detection and four tracking algorithms (BoT-SORT, ByteTrack, Intersection over Union, and Centroid) were used to assess MOT of bycaught Pacific salmon in trawls. All five YOLO12 models are provided as part of this dataset. |
| Purpose: |
Bycatch reduction devices (BRDs) are used in the Alaska walleye pollock (Gadus chalcogrammus) fishery to reduce Pacific salmon (Oncorhynchus spp.) bycatch. Evaluation of BRD effectiveness often requires people to process collected or live-feed video, which can be a tedious, expensive, and time-consuming task. Deep learning can be used to automate the detection, classification, and tracking of fish in videos to support BRD and other fisheries bycatch work. This dataset was developed to evaluate the performance of widely-available, open-source pre-trained object detection models for the task of pollock and salmon detection and multi-object tracking models for salmon tracking. |
Keywords
Theme Keywords
| Thesaurus | Keyword |
|---|---|
| UNCONTROLLED | |
| None | bycatch reduction |
| None | computer vision |
| None | multi-object tracking |
| None | object detection |
| None | trawl fisheries |
Physical Location
| Organization: | Alaska Fisheries Science Center |
|---|---|
| City: | Seattle |
| State/Province: | WA |
| Country: | USA |
| Location Description: |
RACE division, MACE program |
Data Set Information
| Data Set Scope Code: | Data Set |
|---|---|
| Data Set Type: | Imagery |
| Maintenance Frequency: | As Needed |
| Data Presentation Form: | Image (digital) |
| Entity Attribute Overview: |
The dataset includes the subset of video clips that were collected in the commercial pollock fishery in Alaska and annotated for salmon and pollock and the YOLO12 object detection models that were trained, evaluated, and used for MOT tracking algorithms. |
| Data Set Credit: | F/V Pacific Explorer, David Bryan, Deborah Sharpe , Katherine Hellen-Schneider, Matthew Callahan, Connor Fox |
Support Roles
Author
| Date Effective From: | 2026 |
|---|---|
| Date Effective To: | |
| Contact (Organization): | Pacific States Marine Fisheries Commission (PSMFC) |
| Address: | |
| Contact Instructions: |
Lurbur, Moses <mlurbur@gmail.com> |
Co-Author
| Date Effective From: | 2026 |
|---|---|
| Date Effective To: | |
| Contact (Person): | Yochum, Noelle |
| Address: |
7600 Sand Point Way NE, Bldg. 4 Seattle, WA 98115 United States |
| Email Address: | noelle.yochum@noaa.gov |
| Phone: | (206) 526-4432 |
| Mobile: | (916) 719-5920 |
Co-Author
| Date Effective From: | 2026 |
|---|---|
| Date Effective To: | |
| Contact (Person): | Wilson, Katherine |
| Address: |
7600 Sand Point Way NE, Bldg. 4 Seattle, FL 98115 United States |
| Email Address: | katherine.wilson@noaa.gov |
| Phone: | 2065264474 |
Point of Contact
| Date Effective From: | 2026 |
|---|---|
| Date Effective To: | |
| Contact (Person): | Wilson, Katherine |
| Address: |
7600 Sand Point Way NE, Bldg. 4 Seattle, FL 98115 United States |
| Email Address: | katherine.wilson@noaa.gov |
| Phone: | 2065264474 |
Extents
Extent Group 1
| Extent Description: |
All 7 tows from Trip 1 were within this extent. |
|---|
Extent Group 1 / Geographic Area 1
| W° Bound: | -166.03722222222 | |
|---|---|---|
| E° Bound: | -165.59805555556 | |
| N° Bound: | 54.69833333333 | |
| S° Bound: | 54.32472222222 |
Extent Group 1 / Time Frame 1
| Time Frame Type: | Range |
|---|---|
| Start: | 2020-08-07 |
| End: | 2020-08-10 |
Extent Group 2
| Extent Description: |
All 4 tows from trip 2 were within these bounds. |
|---|
Extent Group 2 / Geographic Area 1
| W° Bound: | -165.72888888889 | |
|---|---|---|
| E° Bound: | -165.43055555556 | |
| N° Bound: | 54.78472222222 | |
| S° Bound: | 54.51527777778 |
Extent Group 2 / Time Frame 1
| Time Frame Type: | Range |
|---|---|
| Start: | 2020-08-13 |
| End: | 2020-08-16 |
Extent Group 3
| Extent Description: |
All 26 tows were within this extent. |
|---|
Extent Group 3 / Geographic Area 1
| W° Bound: | -166 | |
|---|---|---|
| E° Bound: | -164.5 | |
| N° Bound: | 55.33333333333 | |
| S° Bound: | 54.33333333333 |
Extent Group 3 / Time Frame 1
| Time Frame Type: | Range |
|---|---|
| Start: | 2019-06-01 |
| End: | 2019-06-30 |
Access Information
| Data License: | CC0-1.0 |
|---|---|
| Data License URL: | https://creativecommons.org/publicdomain/zero/1.0/ |
| Data License Statement: | These data were produced by NOAA and are not subject to copyright protection in the United States. NOAA waives any potential copyright and related rights in these data worldwide through the Creative Commons Zero 1.0 Universal Public Domain Dedication (CC0-1.0). |
| Security Class: | Unclassified |
| Data Access Procedure: |
Video clip frames, annotations, and object detection models can be accessed at https://console.cloud.google.com/storage/browser/nmfs_odp_afsc/RACE/MACE/salmon_pollock_object_detection. |
| Data Access Constraints: |
If using these data, please cite https://doi.org/10.1093/icesjms/fsaf168 and/or https://doi.org/[placeholder] |
Distribution Information
Distribution 1
| Download URL: | https://console.cloud.google.com/storage/browser/nmfs_odp_afsc/RACE/MACE/salmon_pollock_object_detection/ |
|---|---|
| Distributor: | |
| File Name: | 2019-2020 Salmon and Pollock Object Detection dataset |
| Description: |
This folder within the Alaska Fisheries Science Center's Google cloud storage contains the data and object detection models used for the Lurbur et al. 2026 study on multi-object tracking of salmon in trawl videos from the Alaska commercial pollock fishery. The 'annotated_data' folder contains a folder for each of the 184 video clips used in the study that provides video frames as png files and the annotations as a custom COCO json file. The 'models' folder contains the object detection models that were used in the study. The 'documentation' folder contains text files that provide details about the data and the cloud storage file structure. The 'tow_data' folder contains videos and data relevant to the Wilson et al. 2025 study and is not relevant to the Lurbur et al. 2026 study. |
| Distribution Format: | PNG - Portable Network Graphics Format |
| File Size: | <2MB |
| Compression: | Uncompressed |
URLs
URL 1
| URL: | https://github.com/noaa-afsc-mace/salmon_tracking.git |
|---|---|
| Name: | Salmon tracking repo |
| Description: |
Source code for salmon tracking work from Lurbur et al. 2026. |
URL 2
| URL: | https://console.cloud.google.com/storage/browser/nmfs_odp_afsc/RACE/MACE/salmon_pollock_object_detection |
|---|---|
| Name: | Dataset |
| Description: |
Dataset that includes annotated data and models for the Lurbur et al. 2026 study. |
URL 3
| URL: | https://doi.org/10.1016/j.ecoinf.2026.103674 |
|---|---|
| Name: | Towards automated bycatch monitoring: Optimizing and evaluating multi-object tracking of salmon in pollock trawls |
| Description: |
Scientific publication |
Data Quality
| Representativeness: |
Video from within the trawl of the commercial pollock fishery in Alaska and the associated annotations of salmon and pollock. |
|---|---|
| Accuracy: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Analytical Accuracy: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Horizontal Positional Accuracy: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Vertical Positional Accuracy: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Quantitation Limits: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Bias: |
See Wilson et. 2025 publications for details. |
| Comparability: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Completeness Measure: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Precision: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Analytical Precision: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Field Precision: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Sensitivity: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Detection Limit: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Completeness Report: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Conceptual Consistency: |
See Wilson et al. 2025 and Lurbur et al. 2026 publications for details. |
| Quality Control Procedures Employed: |
Annotations were done by trained personnel and reviewed by a lead scientist. |
Data Management
| Have Resources for Management of these Data Been Identified?: | Yes |
|---|---|
| Approximate Percentage of Budget for these Data Devoted to Data Management: | 0 |
| Do these Data Comply with the Data Access Directive?: | No |
| Is Access to the Data Limited Based on an Approved Waiver?: | No |
| Actual or Planned Long-Term Data Archive Location: | Other |
Lineage
| Lineage Statement: |
The video portion of this project was collected onboard the FV Pacific Explorer by Noelle Yochum and Katherine Hellen-Schneider in 2019 and by Connor Fox in 2020 with Sexton housings equipped with Mobius cameras. Processing of video (identifying salmon and entering data) was conducted by David Bryan, Michelle Dyroy, Noelle Yochum, and Katherine Wilson. Video annotation (bounding box tracks of salmon and pollock) was done by Moses Lurbur, Deborah Sharpe, Katherine Hellen-Schneider, and Matthew Callahan. Annotation QA/QC was conducted by Katherine Wilson. |
|---|
Acquisition Information
Instruments
Instrument 1
| Identifier: | Sexton Video Camera System |
|---|---|
| Instrument / Gear: | Instrument |
| Instrument Type: | Video Recorder |
| Description: |
The Sexton video camera system consists of an underwater housing rated to 1000m, 2 LED lights, a Mobius2 Action Camera, and a power supply (either 2 NiMH 19.2v or 2 Li-Ion 14.4v batteries). The Mobius2 camera can record 1800 HD video at 30 frames per second and is suitable for low light scenarios. |
Catalog Details
| Catalog Item ID: | 79020 |
|---|---|
| GUID: | gov.noaa.nmfs.inport:79020 |
| Metadata Record Created By: | Katherine Wilson |
| Metadata Record Created: | 2026-01-20 23:37+0000 |
| Metadata Record Last Modified By: | Abigail McCarthy |
| Metadata Record Last Modified: | 2026-03-31 22:02+0000 |
| Metadata Record Published: | 2026-03-31 |
| Owner Org: | AFSC |
| Metadata Publication Status: | Published Externally |
| Do Not Publish?: | N |
| Metadata Last Review Date: | 2025-09-09 |
| Metadata Review Frequency: | 1 Year |
| Metadata Next Review Date: | 2026-09-09 |