Overview

Background

Human Activity Recognition is beginning to be applied in industrial domains, targeting the improvement of manual labor efficiency. We know processes such as assembly and packaging inside factories or logistic centers still mainly depend on manual workers. To ensure a rapid response to changing demands, this trend is expected to continue. Therefore, quantifying manual labor is a crucial requirement to streamlining existing processes.

Workers inside logistic centers perform a series of sequential tasks to pack items. These working periods consist of actions like reading item labels or assembling the packaging boxes. Understanding details from each of these operations, i.e. its temporal duration or potential abnormalities, is crucial for optimizing the packaging process. However, period uniqueness related to item size or number of items included, make identifying such operation details a challenging task.

Challenge

You’ll develop a model to recognize the operations that conform packaging work with data from 4 IMU streams, keypoint data, etc. The packaging work consists of 10 operations (i.e., activity classes) described below. To quantify the operations as precisely as possible, dense labeling is required. You must predict activity classes for each 1second-long time slot. You can use data from 11 subjects to develop your model. The test data consists of 6 subjects (4 distinct subjects).

If successful, your work will help the ubiquitous research community improve current smart factories and better integrate human factors into the smart factory optimization process.

Task (Technical Details)

Plese visit the following page for more technical details such as task definition, evaluation procedures, and rules.

Prize

A. Cash Prize

The awards ceremony will be held at Percom 2023 WS (BiRD2023). We would like to hand out the cash prizes in this ceremony.

• 1st: 100,000 JPY
• 2nd: 40,000 JPY
• 3rd: 20,000 JPY

B. Travel Fee Support

At least one person from the top-3 top-5 team strongly encouraged to attend the award ceremony. We will support the travel fee for the attendance up to 1 member (up to 750,000JPY/person) from each winner team.

Update: We were able to secure a budget for three people, so we changed our travel fee support from the top-2 to the top-3 teams. (2022-10-11)

Update: The top-5 teams will receive travel support. This means that in addition to the top three teams, one member from the 4th and 5th place teams will also be able to attend Percom2023 with travel support. In addition, the maximum support amount has been changed from 500,000 JPY to 750,000 JPY. (2022-12-31)

Winners Obligations

As a condition to being awarded a Prize, a top-5 winner must fulfill the following obligations. The detail instructions will be sent to top-5 winner after the final submission deadline.

• Submit your code so that we can check for cheating.
• Submit a short report paper that describes the award methodology.

Rules for OpenPack Challenge 2022

A. Registration Required

Please submit team registration form before you join this competition even if you a solo challenger. This is required to get prizes. There are no limitation for the team size. However, if you are creating multiple teams within the same lab, be careful not to violate the rules of PRIVATE SHARING.

When you want to merge your team with other team, please contact OpenPack Challenge Admin Team via email.

B. No Private Sharing Outside Teams

Privately sharing code or data outside of teams is not permitted. It’s OK to share code if made available to all participants on the forum.

C. External Dataset

You may use data other than the competition data to develop and test your submission. However, you will ensure the external data is publicly available to everyone without any cost.

Timeline

Getting Started

Video

Slide

Tools