14,630 research outputs found
Articulated Pose Estimation Using Hierarchical Exemplar-Based Models
Exemplar-based models have achieved great success on localizing the parts of
semi-rigid objects. However, their efficacy on highly articulated objects such
as humans is yet to be explored. Inspired by hierarchical object representation
and recent application of Deep Convolutional Neural Networks (DCNNs) on human
pose estimation, we propose a novel formulation that incorporates both
hierarchical exemplar-based models and DCNNs in the spatial terms.
Specifically, we obtain more expressive spatial models by assuming independence
between exemplars at different levels in the hierarchy; we also obtain stronger
spatial constraints by inferring the spatial relations between parts at the
same level. As our method strikes a good balance between expressiveness and
strength of spatial models, it is both effective and generalizable, achieving
state-of-the-art results on different benchmarks: Leeds Sports Dataset and
CUB-200-2011.Comment: 8 pages, 6 figure
Topological Foundations of Cognitive Science
A collection of papers presented at the First International Summer Institute in Cognitive Science, University at Buffalo, July 1994, including the following papers:
** Topological Foundations of Cognitive Science, Barry Smith
** The Bounds of Axiomatisation, Graham White
** Rethinking Boundaries, Wojciech Zelaniec
** Sheaf Mereology and Space Cognition, Jean Petitot
** A Mereotopological Definition of 'Point', Carola Eschenbach
** Discreteness, Finiteness, and the Structure of Topological Spaces, Christopher Habel
** Mass Reference and the Geometry of Solids, Almerindo E. Ojeda
** Defining a 'Doughnut' Made Difficult, N .M. Gotts
** A Theory of Spatial Regions with Indeterminate Boundaries, A.G. Cohn and N.M. Gotts
** Mereotopological Construction of Time from Events, Fabio Pianesi and Achille C. Varzi
** Computational Mereology: A Study of Part-of Relations for Multi-media Indexing, Wlodek Zadrozny and Michelle Ki
Multi-Cue Structure Preserving MRF for Unconstrained Video Segmentation
Video segmentation is a stepping stone to understanding video context. Video
segmentation enables one to represent a video by decomposing it into coherent
regions which comprise whole or parts of objects. However, the challenge
originates from the fact that most of the video segmentation algorithms are
based on unsupervised learning due to expensive cost of pixelwise video
annotation and intra-class variability within similar unconstrained video
classes. We propose a Markov Random Field model for unconstrained video
segmentation that relies on tight integration of multiple cues: vertices are
defined from contour based superpixels, unary potentials from temporal smooth
label likelihood and pairwise potentials from global structure of a video.
Multi-cue structure is a breakthrough to extracting coherent object regions for
unconstrained videos in absence of supervision. Our experiments on VSB100
dataset show that the proposed model significantly outperforms competing
state-of-the-art algorithms. Qualitative analysis illustrates that video
segmentation result of the proposed model is consistent with human perception
of objects
Topological Schemas of Memory Spaces
Hippocampal cognitive map---a neuronal representation of the spatial
environment---is broadly discussed in the computational neuroscience literature
for decades. More recent studies point out that hippocampus plays a major role
in producing yet another cognitive framework that incorporates not only
spatial, but also nonspatial memories---the memory space. However, unlike
cognitive maps, memory spaces have been barely studied from a theoretical
perspective. Here we propose an approach for modeling hippocampal memory spaces
as an epiphenomenon of neuronal spiking activity. First, we suggest that the
memory space may be viewed as a finite topological space---a hypothesis that
allows treating both spatial and nonspatial aspects of hippocampal function on
equal footing. We then model the topological properties of the memory space to
demonstrate that this concept naturally incorporates the notion of a cognitive
map. Lastly, we suggest a formal description of the memory consolidation
process and point out a connection between the proposed model of the memory
spaces to the so-called Morris' schemas, which emerge as the most compact
representation of the memory structure.Comment: 24 pages, 8 Figures, 1 Suppl. Figur
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