ACML2019 workshop on Machine Learning for Trajectory, Activity, and Behavior (ACML-TAB2019)

Back to list of workshops

Recent advances in sensing technology have made it possible to collect vast amounts of trajectories, activities and behavior data from humans, animals, and vehicles. Smart devices and visual tracking are used to capture the data of players in the sports scene and vehicles in the city for skill assessment or resource allocations. Small GPS and acceleration loggers collect behavioral data from animals in the wild, such as birds and bats, to better understand the ecology of animals. Therefore, machine learning techniques have been developed to recognize, analyze, and predict the trajectory, activity, and behavior of various targets.

This workshop provides a place for engineers, computer scientists, biologist, and neuroscientists to discuss machine learning and related methods for trajectory, activity, and behavior data collected from various sources, such as humans, animals, insects, and automobiles. The topics of interest include, but are not limited to:

  • Machine learning, time series analysis, data mining, and knowledge extraction for trajectory/activity/behavior data
  • Modeling, collecting, data preparation and labeling for trajectory/activity/behavior data
  • Systems and applications of monitoring and recognition systems for trajectory/activity/behavior data
  • Localization, recognition, prediction, and visualization for trajectory/activity/behavior data

This workshop invites submissions of one or two page abstracts in PDF format for oral or poster presentations.

  • Submission deadline: 2019/Sep/30
  • Workshop date: 2019/Nov/17 (Sun)

There will be no published proceedings, and the submissions will be posted on the workshop website. All submissions, if relevant to the topics, are welcome to present in a poster session. (there is no reviewing, but organizers will select in case of many submissions or out-of-scope.)