@article{Kulkarni-IJCV-2014,
  IS = { zkontrolovano 26 Jun 2015 },
UPDATE   = { 2015-06-11 },
   author = {Kulkarni, Kaustubh and Evangelidis,  Georgios and Cech, Jan and Horaud,  Radu},
   title = {Continuous Action Recognition Based on Sequence Alignment},
   journal = {International Journal of Computer Vision},
   ISSN = {0920-5691},
   DOI = {10.1007/s11263-014-0758-9},
year     = { 2015 },
volume   = { 112 },
number   = { 1 },
pages    = { 90--114 },
   project = {FP7-ICT-247525 HUMAVIPS, GACR P103/12/G084},
   ANNOTE = {{Continuous action recognition is more challenging than
                  isolated recognition beca use classification and
                  segmentation must be simultaneously carried out. We
                  build on the well k nown dynamic time warping
                  framework and devise a novel visual alignment
                  technique, namely dyna mic frame warping (DFW),
                  which performs isolated recognition based on
                  per-frame representation of videos, and on aligning
                  a test sequence with a model sequence. Moreover, we
                  propose two ex tensions which enable to perform
                  recognition concomitant with segmentation, namely
                  one-pass DF W and two-pass DFW. These two methods
                  have their roots in the domain of continuous
                  recognition of speech and, to the best of our
                  knowledge, their extension to continuous visual
                  action reco gnition has been overlooked. We test and
                  illustrate the proposed techniques with a recently
                  re leased dataset (RAVEL) and with two public-domain
                  datasets widely used in action recognition (
                  Hollywood-1 and Hollywood-2).We also compare the
                  performances of the proposed isolated and con
                  tinuous recognition algorithms with several recently
                  published methods.}},
   keywords = {Action recognition, Video segmentation, Example-based
                  recognition, Template mat ching, Dynamic
                  programming, Dynamic time warping, Bag of words},
   url = {http://dx.doi.org/10.1007/s11263-014-0758-9},
   publisher = {Springer},
   address = {Cham, Switzerland},
affiliation = { NULL-NULL-13133-NULL },
month       = { March },
}