%0 Conference Paper %1 65eb3452a2b74bcb8ee158a91eb96d3b %A Oyshi, Marzan Tasnim %A Vogt, Sebastian %A Gumhold, Stefan %B CHI 2023 - Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems %D 2023 %E Schmidt, Albrecht %E Väänänen, Kaisa %E Goyal, EditoTesh %E Kristensson, Per Ola %E Peters, Anicia %E Mueller, Stefanie %E Williamson, Julie R. %E Wilson, Max L. %I Association for Computing Machinery %K topic_visualcomputing FIS_scads data labeling labeling, manual sequence video %R 10.1145/3544548.3581185 %T TmoTA: Simple, Highly Responsive Tool for Multiple Object Tracking Annotation %U https://chi2023.acm.org/ %X Machine learning is applied in a multitude of sectors with very impressive results. This success is due to the availability of an ever-growing amount of data acquired by omnipresent sensor devices and platforms on the internet. But there is a scarcity of labeled data which is required for most ML methods. However, generation of labeled data requires much time and resources. In this paper, we propose a portable, Open Source, simple and responsive manual Tool for 2D multiple object Tracking Annotation (TmoTA). Besides responsiveness, our tool design provides several features like view centering and looped playback that speed up the annotation process. We evaluate our proposed tool by comparing TmoTA with the widely used manual labeling tools CVAT, Label Studio, and two semi-automated tools Supervisely and VATIC with respect to object labeling time and accuracy. The evaluation includes a user study and pre-case studies showing that the annotation time per object frame can be reduced by 20% to 40% over the first 20 annotated objects compared to the manual labeling tools.

@inproceedings{65eb3452a2b74bcb8ee158a91eb96d3b, abstract = {Machine learning is applied in a multitude of sectors with very impressive results. This success is due to the availability of an ever-growing amount of data acquired by omnipresent sensor devices and platforms on the internet. But there is a scarcity of labeled data which is required for most ML methods. However, generation of labeled data requires much time and resources. In this paper, we propose a portable, Open Source, simple and responsive manual Tool for 2D multiple object Tracking Annotation (TmoTA). Besides responsiveness, our tool design provides several features like view centering and looped playback that speed up the annotation process. We evaluate our proposed tool by comparing TmoTA with the widely used manual labeling tools CVAT, Label Studio, and two semi-automated tools Supervisely and VATIC with respect to object labeling time and accuracy. The evaluation includes a user study and pre-case studies showing that the annotation time per object frame can be reduced by 20% to 40% over the first 20 annotated objects compared to the manual labeling tools.}, added-at = {2024-11-28T16:27:18.000+0100}, author = {Oyshi, {Marzan Tasnim} and Vogt, Sebastian and Gumhold, Stefan}, biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/21b514499645d3070da167d75006ad584/scadsfct}, booktitle = {CHI 2023 - Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems}, day = 19, doi = {10.1145/3544548.3581185}, editor = {Schmidt, Albrecht and V{\"a}{\"a}n{\"a}nen, Kaisa and Goyal, {EditoTesh } and Kristensson, {Per Ola } and Peters, {Anicia } and Mueller, {Stefanie } and Williamson, {Julie R. } and Wilson, {Max L. }}, interhash = {c3144dce4c1d76ca5ebf677f2c83e723}, intrahash = {1b514499645d3070da167d75006ad584}, keywords = {topic_visualcomputing FIS_scads data labeling labeling, manual sequence video}, language = {English}, month = apr, note = {Publisher Copyright: {\textcopyright} 2023 ACM.; CHI Conference on Human Factors in Computing Systems 2023, CHI 2023 ; Conference date: 23-04-2023 Through 28-04-2023}, publisher = {Association for Computing Machinery}, series = {CHI: Conference on Human Factors in Computing Systems}, timestamp = {2024-11-28T17:41:41.000+0100}, title = {TmoTA: Simple, Highly Responsive Tool for Multiple Object Tracking Annotation}, url = {https://chi2023.acm.org/}, year = 2023 }