IS = { zkontrolovano 15 Jan 2013 },
  UPDATE  = { 2012-05-25 },
author =      {{\v S}ochman, Jan and Matas, Ji{\v r}{\'\i}},
title =       {Motion-Based Tracking of Multiple Low-Relative-Depth Objects},
institution = {Center for Machine Perception, K13133 FEE
              Czech Technical University},
address =     {Prague, Czech Republic},
year =        {2012},
month =       {May},
type =        {Research Report},
number =      {CTU--CMP--2012--10},
issn =        {1213-2365},
pages =       {13},
figures =     {5},
authorship =  {50-50},
psurl       = {},
project =     {GACR P103/12/G084, HS Toyota},
annote =      {In this report, we present a method for online tracking
  of multiple rigid low-relative-depth objects or object surfaces from
  a single moving or static camera. The method determines the number
  of tracked entities in the scene automatically and initialises them
  without any human interaction or by running a specific object
  detector.  Tracking is formulated as an energy-based multi-model
  fitting problem based on displacement of a semi-dense set of local
  Lukas-Kanade trackers. An over-complete set of motion models is
  generated in each frame and fitted considering the motion
  similarity. For each detected surface the motion model is propagated
  in time and to ensure temporal consistency and locality of the
  tracked entities in the scene two novel energy terms are
  introduced. We demonstrate the abilities of the proposed algorithm
  on several long real-world sequences. The algorithm works at 2-6fps
  depending on the complexity of the scene.},
keywords =    {tracking, motion segmentation, on-line},
note =        {Confidential},