2nd Workshop on
October 2016, Amsterdam
In Conjunction with the European Conference in Computer Vision (ECCV) 2016
Benchmarking multi-target tracking 2016

In the recent past, the computer vision community has accepted several centralized benchmarks for numerous tasks including object detection, pedestrian detection, 3D reconstruction, optical flow, single-object short-term tracking, and stereo estimation. Despite potential pitfalls of such benchmarks, they have proved to be extremely helpful to advance the state-of-the-art in the respective research fields. Interestingly, there has been rather limited work on the standardization of multiple target tracking evaluation. One of the few exceptions is the well-known PETS dataset, targeted primarily at surveillance applications. Even for this widely used benchmark, a common technique for presenting tracking results to date involves using different subsets of the available data, inconsistent model training and varying evaluation scripts.

In this workshop we would like to continue our goal towards a unified framework towards more meaningful quantification of multi-target tracking. Building on our first edition, we are determined to provide a stable infrastructure to eliminate current limitations. Its key strength is twofold. On the one hand, a dynamic framework that leverages the power of crowd-sourcing by accepting new datasets, annotations and even new evaluation metrics will ensure an up-to-date benchmark that constantly stays at the edge of the technological advance. On the other hand, all participants will be using exactly the same detection sets, annotations and evaluation procedures, hence guaranteeing a fair comparison.

During the workshop, we expect to collect participants’ experience regarding both the existing and the new 2016 datasets, the available infrastructure and to discuss further improvement strategies. We believe that our efforts to produce realistic data as well as the continuing workshop series will push the community towards a more unified and meaningful quantification of multi-target tracking.

Call for Papers

This is the 2nd Workshop on Benchmarking Multi-Target Tracking (BMTT), held in conjunction with the European Conference in Computer Vision (ECCV) in Amsterdam on October 9th, 2016.

We are looking forward to welcoming researchers and industry affiliates in computer vision, machine learning, image analysis and related fields, to present and discuss their work. A single-track program with keynote talks, oral and poster presentations shall provide ample opportunities for scientific exchange and discussion.

BMTT 2016 invites submissions of high-quality research results as full papers as well as high-impact existing work as extended abstracts.

Paper submission deadline: August 10th, 2016
Notification of acceptance: August 25th, 2016
Workshop date: October 9th, 2016

Full-paper submissions will undergo a selective double-blind peer-review process, normally by three members of the international reviewing committee. Submitted papers will be refereed on their scientific originality and relevance, presentation and empirical results. For details on formatting, submission and paper policies please see the instructions for authors.

Topics include, but are not limited to:

  • Multi-target tracking
  • Video segmentation
  • Visual surveillance and tracking in crowded scenes
  • Tracking for sports analysis
  • Real-time tracking
  • Robust data association
  • Action recognition and localization
  • Abnormal activity recognition
  • Multi-class tracking and holistic scene understanding
  • Evaluation criteria and metrics
  • Dataset proposals and bias analysis

As organizers of BMTT 2016 we are looking forward to your contributions and to welcoming you in Amsterdam.

Laura Leal-Taixé
Anton Milan
Ian Reid
Daniel Cremers
Stefan Roth
Konrad Schindler



Participating institutions