Continuous Action Recognition Based on Sequence Alignment

Continuous action recognition is more challenging than isolated recognition because classification and segmentation must be simultaneously carried out. We build on the well known dynamic time warping (DTW) framework and devise a novel visual alignment technique, namely dynamic 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 extensions which enable to perform recognition concomitant with segmentation, namely one-pass DFW 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 recognition has been overlooked. We test and illustrate the proposed techniques with a recently released 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 continuous recognition algorithms with several recently published methods

Rapid magnetic oscillations and magnetic breakdown in quasi-1D conductors

We review the physics of magnetic quantum oscillations in quasi-one dimensional conductors with an open Fermi surface, in the presence of modulated order. We emphasize the difference between situations where a modulation couples states on the same side of the Fermi surface and a modulation couples states on opposite sides of the Fermi surface. We also consider cases where several modulations coexist, which may lead to a complex reorganization of the Fermi surface. The interplay between nesting effects and magnetic breakdown is discussed. The experimental situation is reviewed.Comment: 10 pages, 8 figures, Contribution to the memorial issue in honor of J. Friedel, C. R. Acad. Sci. Pari