On the fine structure of the quiet solar \Ca II K atmosphere

We investigate the morphological, dynamical, and evolutionary properties of the internetwork and network fine structure of the quiet sun at disk centre. The analysis is based on a $\sim$6 h time sequence of narrow-band filtergrams centred on the inner-wing \Ca II K$_{\rm 2v}$ reversal at 393.3 nm. The results for the internetwork are related to predictions derived from numerical simulations of the quiet sun. The average evolutionary time scale of the internetwork in our observations is 52 sec. Internetwork grains show a tendency to appear on a mesh-like pattern with a mean cell size of $\sim$4-5 arcsec. Based on this size and the spatial organisation of the mesh we speculate that this pattern is related to the existence of photospheric downdrafts as predicted by convection simulations. The image segmentation shows that typical sizes of both network and internetwork grains are in the order of 1.6 arcs.Comment: 8 pages, 9 figure

Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception

Choosing an appropriate set of stimuli is essential to characterize the response of a sensory system to a particular functional dimension, such as the eye movement following the motion of a visual scene. Here, we describe a framework to generate random texture movies with controlled information content, i.e., Motion Clouds. These stimuli are defined using a generative model that is based on controlled experimental parametrization. We show that Motion Clouds correspond to dense mixing of localized moving gratings with random positions. Their global envelope is similar to natural-like stimulation with an approximate full-field translation corresponding to a retinal slip. We describe the construction of these stimuli mathematically and propose an open-source Python-based implementation. Examples of the use of this framework are shown. We also propose extensions to other modalities such as color vision, touch, and audition

Segmental Spatiotemporal CNNs for Fine-grained Action Segmentation

Joint segmentation and classification of fine-grained actions is important for applications of human-robot interaction, video surveillance, and human skill evaluation. However, despite substantial recent progress in large-scale action classification, the performance of state-of-the-art fine-grained action recognition approaches remains low. We propose a model for action segmentation which combines low-level spatiotemporal features with a high-level segmental classifier. Our spatiotemporal CNN is comprised of a spatial component that uses convolutional filters to capture information about objects and their relationships, and a temporal component that uses large 1D convolutional filters to capture information about how object relationships change across time. These features are used in tandem with a semi-Markov model that models transitions from one action to another. We introduce an efficient constrained segmental inference algorithm for this model that is orders of magnitude faster than the current approach. We highlight the effectiveness of our Segmental Spatiotemporal CNN on cooking and surgical action datasets for which we observe substantially improved performance relative to recent baseline methods.Comment: Updated from the ECCV 2016 version. We fixed an important mathematical error and made the section on segmental inference cleare

Tracing the Peculiar Dark Matter Structure in the Galaxy Cluster CL 0024+17 with Intracluster Stars and Gas

ICL is believed to originate from the stars stripped from cluster galaxies. They are no longer gravitationally bound to individual galaxies, but to the cluster, and their smooth distribution potentially makes them serve as much denser tracers of the cluster dark matter than the sparsely distributed cluster galaxies. We present our study of the ICL in Cl 0024+17 using both ACS and Subaru data, where we previously reported discovery of a ringlike dark matter structure with gravitational lensing. The ACS images provide much lower sky levels than ground data, and enable us to measure relative variation of surface brightness reliably. This analysis is repeated with the Subaru images to examine if consistent features are recovered despite different reduction scheme and instrumental characteristics. We find that the ICL profile clearly resembles the peculiar mass profile, which stops decreasing at r~50" (~265 kpc) and slowly increases until it turns over at r~75" (~397 kpc). This feature is seen in both ACS and Subaru images for nearly all available passband images while the features are stronger in red filters. The consistency across different filters and instruments strongly rules out the possibility that the feature might come from any residual, uncorrected calibration errors. In addition, our re-analysis of the cluster X-ray data shows that the peculiar mass structure is also indicated by a non-negligible bump in the intracluster gas profile when the geometric center of the dark matter ring, not the peak of the X-ray emission, is chosen as the center of the radial bin. The location of the gas ring is closer to the center by ~15" (~80 kpc), raising an interesting possibility that the ring-like structure is expanding and the gas ring is lagging behind perhaps because of the ram pressure if both features in mass and gas share the same dynamical origin.Comment: Accepted to ApJ for publicatio

Laminar Cortical Dynamics of Visual Form and Motion Interactions During Coherent Object Motion Perception

How do visual form and motion processes cooperate to compute object motion when each process separately is insufficient? A 3D FORMOTION model specifies how 3D boundary representations, which separate figures from backgrounds within cortical area V2, capture motion signals at the appropriate depths in MT; how motion signals in MT disambiguate boundaries in V2 via MT-to-Vl-to-V2 feedback; how sparse feature tracking signals are amplified; and how a spatially anisotropic motion grouping process propagates across perceptual space via MT-MST feedback to integrate feature-tracking and ambiguous motion signals to determine a global object motion percept. Simulated data include: the degree of motion coherence of rotating shapes observed through apertures, the coherent vs. element motion percepts separated in depth during the chopsticks illusion, and the rigid vs. non-rigid appearance of rotating ellipses.Air Force Office of Scientific Research (F49620-01-1-0397); National Geospatial-Intelligence Agency (NMA201-01-1-2016); National Science Foundation (BCS-02-35398, SBE-0354378); Office of Naval Research (N00014-95-1-0409, N00014-01-1-0624