71 research outputs found
Affine Subspace Representation for Feature Description
This paper proposes a novel Affine Subspace Representation (ASR) descriptor
to deal with affine distortions induced by viewpoint changes. Unlike the
traditional local descriptors such as SIFT, ASR inherently encodes local
information of multi-view patches, making it robust to affine distortions while
maintaining a high discriminative ability. To this end, PCA is used to
represent affine-warped patches as PCA-patch vectors for its compactness and
efficiency. Then according to the subspace assumption, which implies that the
PCA-patch vectors of various affine-warped patches of the same keypoint can be
represented by a low-dimensional linear subspace, the ASR descriptor is
obtained by using a simple subspace-to-point mapping. Such a linear subspace
representation could accurately capture the underlying information of a
keypoint (local structure) under multiple views without sacrificing its
distinctiveness. To accelerate the computation of ASR descriptor, a fast
approximate algorithm is proposed by moving the most computational part (ie,
warp patch under various affine transformations) to an offline training stage.
Experimental results show that ASR is not only better than the state-of-the-art
descriptors under various image transformations, but also performs well without
a dedicated affine invariant detector when dealing with viewpoint changes.Comment: To Appear in the 2014 European Conference on Computer Visio
Stimulus-dependent maximum entropy models of neural population codes
Neural populations encode information about their stimulus in a collective
fashion, by joint activity patterns of spiking and silence. A full account of
this mapping from stimulus to neural activity is given by the conditional
probability distribution over neural codewords given the sensory input. To be
able to infer a model for this distribution from large-scale neural recordings,
we introduce a stimulus-dependent maximum entropy (SDME) model---a minimal
extension of the canonical linear-nonlinear model of a single neuron, to a
pairwise-coupled neural population. The model is able to capture the
single-cell response properties as well as the correlations in neural spiking
due to shared stimulus and due to effective neuron-to-neuron connections. Here
we show that in a population of 100 retinal ganglion cells in the salamander
retina responding to temporal white-noise stimuli, dependencies between cells
play an important encoding role. As a result, the SDME model gives a more
accurate account of single cell responses and in particular outperforms
uncoupled models in reproducing the distributions of codewords emitted in
response to a stimulus. We show how the SDME model, in conjunction with static
maximum entropy models of population vocabulary, can be used to estimate
information-theoretic quantities like surprise and information transmission in
a neural population.Comment: 11 pages, 7 figure
Clonal analysis of Notch1-expressing cells reveals the existence of unipotent stem cells that retain long-term plasticity in the embryonic mammary gland.
Recent lineage tracing studies have revealed that mammary gland homeostasis relies on unipotent stem cells. However, whether and when lineage restriction occurs during embryonic mammary development, and which signals orchestrate cell fate specification, remain unknown. Using a combination of in vivo clonal analysis with whole mount immunofluorescence and mathematical modelling of clonal dynamics, we found that embryonic multipotent mammary cells become lineage-restricted surprisingly early in development, with evidence for unipotency as early as E12.5 and no statistically discernable bipotency after E15.5. To gain insights into the mechanisms governing the switch from multipotency to unipotency, we used gain-of-function Notch1 mice and demonstrated that Notch activation cell autonomously dictates luminal cell fate specification to both embryonic and basally committed mammary cells. These functional studies have important implications for understanding the signals underlying cell plasticity and serve to clarify how reactivation of embryonic programs in adult cells can lead to cancer.Wellcome Trus
A Synaptic Mechanism for Temporal Filtering of Visual Signals
The visual system transmits information about fast and slow changes in light intensity through separate neural pathways. We used in vivo imaging to investigate how bipolar cells transmit these signals to the inner retina. We found that the volume of the synaptic terminal is an intrinsic property that contributes to different temporal filters. Individual cells transmit through multiple terminals varying in size, but smaller terminals generate faster and larger calcium transients to trigger vesicle release with higher initial gain, followed by more profound adaptation. Smaller terminals transmitted higher stimulus frequencies more effectively. Modeling global calcium dynamics triggering vesicle release indicated that variations in the volume of presynaptic compartments contribute directly to all these differences in response dynamics. These results indicate how one neuron can transmit different temporal components in the visual signal through synaptic terminals of varying geometries with different adaptational properties
2D Articulated Human Pose Estimation and Retrieval in (Almost) Unconstrained Still Images
Abstract We present a technique for estimating the spatial layout of humans in still images—the position of the head, torso and arms. The theme we explore is that once a person is localized using an upper body detector, the search for their body parts can be considerably simplified using weak constraints on position and appearance arising from that detection. Our approach is capable of estimating upper body pose in highly challenging uncontrolled images, without prior knowledge of background, clothing, lighting, or the location and scale of the person in the image. People are only required to be upright and seen from the front or the back (not side). We evaluate the stages of our approach experimentally using ground truth layout annotation on a variety of challenging material, such as images from the PASCAL VOC 2008 challenge and video frames from TV shows and feature films. We also propose and evaluate techniques for searching a video dataset for people in a specific pose. To this end, we develop three new pose descriptors and compare their clas
Synaptic and circuit mechanisms promoting broadband transmission of olfactory stimulus dynamics
Sensory stimuli fluctuate on many timescales. However, short-term plasticity causes synapses to act as temporal filters, limiting the range of frequencies they can transmit. How synapses in vivo might transmit a range of frequencies in spite of short-term plasticity is poorly understood. The first synapse in the Drosophila olfactory system exhibits short-term depression, and yet can transmit broadband signals. Here we describe two mechanisms that broaden the frequency characteristics of this synapse. First, two distinct excitatory postsynaptic currents transmit signals on different timescales. Second, presynaptic inhibition dynamically updates synaptic properties to promote accurate transmission of signals across a wide range of frequencies. Inhibition is transient but grows slowly, and simulations show that these two features of inhibition promote broadband synaptic transmission. Dynamic inhibition is often thought to restrict the temporal patterns that a neuron responds to, but our results illustrate a different idea: inhibition can expand the bandwidth of neural coding
Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina
When visual contrast changes, retinal ganglion cells adapt by adjusting their sensitivity as well as their temporal filtering characteristics. The latter has classically been described by contrast-induced gain changes that depend on temporal frequency. Here, we explored a new perspective on contrast-induced changes in temporal filtering by using spike-triggered covariance analysis to extract multiple parallel temporal filters for individual ganglion cells. Based on multielectrode-array recordings from ganglion cells in the isolated salamander retina, we found that contrast adaptation of temporal filtering can largely be captured by contrast-invariant sets of filters with contrast-dependent weights. Moreover, differences among the ganglion cells in the filter sets and their contrast-dependent contributions allowed us to phenomenologically distinguish three types of filter changes. The first type is characterized by newly emerging features at higher contrast, which can be reproduced by computational models that contain response-triggered gain-control mechanisms. The second type follows from stronger adaptation in the Off pathway as compared to the On pathway in On-Off-type ganglion cells. Finally, we found that, in a subset of neurons, contrast-induced filter changes are governed by particularly strong spike-timing dynamics, in particular by pronounced stimulus-dependent latency shifts that can be observed in these cells. Together, our results show that the contrast dependence of temporal filtering in retinal ganglion cells has a multifaceted phenomenology and that a multi-filter analysis can provide a useful basis for capturing the underlying signal-processing dynamics
transport planning
Knowing exactly the value of time (VoT) for an individual may be a focus, resultant or definer in transportation planning. In a conventional transit planning paradigm, the decisions that have to be primarily implemented, along with the implementation programs, are determined through heuristic rather than analytical methods. Calculation of the VoT for each zone and scrutiny of these values through the correlation of transit surveys may be crucial in the process of determining investible zones. In the implementation process, the VoT for a zone may be evaluated as a primary selection indicator and thus efficient use of resources may be provided and sustainable development may be ensured. In this study, transit surveys were categorised and VoT estimates were then compared. The investments and interventions generated by evaluating the needs, complaints and expectations of transit users in different zones were sorted by considering the VoT. An analytical model was thus generated for transit planners, policy-makers and decision-makers to determine primarily investable zones in the implementation levels of urban transit planning. A case study revealed that reliability, driver behaviour, route and stop condition indicators provide consistency in selecting the zone priority.C1 [Gulhan, Gorkem] Pamukkale Univ, Fac Architecture & Design, Dept Urban & Reg Planning, Denizli, Turkey.[Ozuysal, Mustafa] Dokuz Eylul Univ, Engn Fac, Dept Civil Engn, Transportat Div, Izmir, Turkey
Robust perception for aerial inspection: Adaptive and on-line techniques
This chapter explains an adaptive on-line object detection and classification technique for robust perception due to varying scene conditions, for example
partial cast shadows, change on the illumination conditions or changes in the angle
of the object target view. This approach continuously updates the target model upon
arrival of new data, being able to adapt to dynamic situations. The method uses an
on-line learning technique that works on real-time and it is continuously updated in
order to adapt to potential changes undergone by the target object. The method can
run in real-time
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