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Explicitly Task Oriented Probabilistic Active Vision for a Mobile Robot
[chapter]
2009
Lecture Notes in Computer Science
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In the presented work, an explicitly task oriented probabilistic active vision system is proposed. ...
As a test-bed for the presented active vision approach, we selected a robot soccer attention problem: goal covering by a goalie player. ...
Conclusions We have presented a probabilistic and explicitly task oriented active vision system which is able to select in which object the robot should focus. ...
doi:10.1007/978-3-642-02921-9_8
fatcat:nmfhfo6dwnezdc7ynrwhgna6hu
Pattern Classification and Analysis of Brain Maps through fMRI data with Multiple Methods
2010
International Journal of Computer Applications
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The fMRI data is huge, dimensionally dissimilar for different orientation data and also show a lot of variation in the data acquired for different subjects for similar activities. ...
The use of individually generated activation maps with SPM allows for better scalability to very large subject pools and it has the potential to integrate data at the activation map level that would be ...
The visiomemory task involves both bilateral vision task and also the non bilateral memory task. ...
doi:10.5120/490-801
fatcat:wmoati23fbccffxgrdru3muzrm
If perception is probabilistic, why does it not seem probabilistic?
2018
Philosophical Transactions of the Royal Society of London. Biological Sciences
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(Visual data are often taken to be activations in early vision.) ...
If there are many samples, the problem this article started with arises: The samples will be samples of different orientations, so why does not vision reflect all the samples? ...
doi:10.1098/rstb.2017.0341
pmid:30061455
fatcat:vmksf3bypjdm7jrh3sivsc32we
Guest editorial: Special issue on active perception
2018
Autonomous Robots
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Active perception involves controlling sensor parameters to achieve a sensing task. ...
Sensing modalities include monocular vision, stereo vision, ...
The special issue was motivated by the workshop "Scaling Up Active Perception," organized by Yiannis Aloimonos, Andrea Censi, Kostas Daniilidis, Volkan Isler, and Stefano Soatto (in alphabetical order) ...
doi:10.1007/s10514-018-9695-8
fatcat:x7usikxz7ff7fius5swznswmfi
SPATIAL AND TEMPORAL ELEMENTS OF ANTICIPATION CONSISTENCY OF CHILDREN WITH GENERAL SPEECH RETARDATION
2014
American Journal of Applied Sciences
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Thus, we face the task to identify the causes of school de-adaptation of children who have speech pathology. ...
We observed a very low level of development of motor coordination of children with general speech underdevelopment, which level is considered as the reflection of the probabilistic forecast on the level ...
All tasks of the graphic test targeted detection of the development of fine motor skills of hands and coordination of vision and hand motion. ...
doi:10.3844/ajassp.2014.1031.1035
fatcat:rv3iqrbeqjctpmu5kbyskl4kjm
Learning probabilistic discriminative models of grasp affordances under limited supervision
2010
2010 IEEE/RSJ International Conference on Intelligent Robots and Systems
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This paper addresses the problem of learning and efficiently representing discriminative probabilistic models of object-specific grasp affordances particularly in situations where the number of labeled ...
Experimental evaluation shows that combining active and semi-supervised learning is favorable in the existence of to an oracle. ...
In this paper, we investigate learning probabilistic models of grasp affordances for an autonomous robot equipped with a 3D vision system (see Figure I ). ...
doi:10.1109/iros.2010.5650088
dblp:conf/iros/ErkanKDAPP10
fatcat:2gii55sqs5cu7pce22mp7ouewy
Activity Recognition Using Histogram of Oriented Gradient Pattern History
2014
International Journal of Computer Science Engineering and Information Technology
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Human activity recognition is an important task in computer vision because it has many application areas such as, healthcare, security, entertainment, and tactical scenarios. ...
We have experimented with video data of human activity in real environments for three different tasks (browsing, reading, and writing). ...
INTRODUCTION Recognizing human activity or task from real-time video data is one of the promising and challenging applications of computer vision. ...
doi:10.5121/ijcseit.2014.4403
fatcat:7mpeq2amljcfraewpw6lf6ud5m
Volumetric Object Reconstruction in Multi-Camera Scenarios
2019
Jornada de Jóvenes Investigadores del I3A
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On the one hand, active vision could be taken as a viable alternative. This technique may require using a vision-based sensor, mounted on a mobile robot, providing dense 3D input data. ...
However, one of the main challenges involved in active vision are deformable or mobile objects, which requires an instantaneous perception of the object. ...
doi:10.26754/jji-i3a.003572
fatcat:v5jyem6ipjgargnuzaqh6hraga
Collective Activity Detection Using Hinge-loss Markov Random Fields
2013
2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops
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We propose hinge-loss Markov random fields (HL-MRFs), a powerful class of continuous-valued graphical models, for high-level computer vision tasks. ...
We apply HL-MRFs to the task of activity detection, using principles of collective classification. Our model is simple, intuitive and interpretable. ...
Conclusion We have shown that HL-MRFs are a powerful class of models for high-level computer vision tasks. When combined with PSL, designing probabilistic models is easy and intuitive. ...
doi:10.1109/cvprw.2013.157
dblp:conf/cvpr/LondonKBHGD13
fatcat:ee6bi3pdmndttljkyx2ugrcxhu
The implications of perception as probabilistic inference for correlated neural variability during behavior
[article]
2015
arXiv
pre-print
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Starting from the old idea of perception as probabilistic inference, we show how to use knowledge of the psychophysical task to make easily testable predictions for the impact that feedback signals have ...
of sensory processing, including the task-dependence of neural response correlations, and the diverging time courses of choice probabilities and psychophysical kernels. ...
as probabilistic inference even though the brain's internal model for general vision is unknown. ...
arXiv:1409.0257v2
fatcat:h2sr4btjozf6thos73ixv6najm
What Do Models of Visual Perception Tell Us about Visual Phenomenology?
[chapter]
2022
Neuroscience and Philosophy
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Although a single number could be used to represent a probability computed at a previous stage, here we use "probabilistic" to refer to the representational stage at which the probability is computed. ...
For example, in an orientation discrimination task, the sensory stage might encode the stimulus orientation as a continuous variable, whereas the decision stage converts that graded sensory response to ...
Models of Visual Perception and Decision Making Here, we consider four widely used vision models: (1) signal detection theory (SDT), (2) drift diffusion models (DDM), (3) probabilistic population codes ...
doi:10.7551/mitpress/12611.003.0014
fatcat:pgbn2w4luzfotcyqzjhdbfc6e4
Adaptive precision pooling of model neuron activities predicts the efficiency of human visual learning
2009
Journal of Vision
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When performing a perceptual task, precision pooling occurs when an organism's decisions are based on the activities of a small set of highly informative neurons. ...
We trained human subjects on a visual slant discrimination task and found their performances to be suboptimal relative to an ideal probabilistic observer. Why were subjects suboptimal learners? ...
In addition, consider the subset of MT neurons whose activities are informative for this task, such as neurons that are reliably more active with 0-stimuli than with 3-stimuli. ...
doi:10.1167/9.4.22
pmid:19757931
fatcat:2ibvquwqsjeyhblqprjjdkwhvq
Striatal dopaminergic modulation of reinforcement learning predicts reward—oriented behavior in daily life
2017
Biological Psychology
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We therefore combined, for the first time, a DA D 2/3 receptor [ 18 F]fallypride PET during a probabilistic reinforcement learning (RL) task with a six day ecological momentary assessments (EMA) of reward-related ...
Furthermore, individual variability in the extent of reward-induced DA release in the right caudate nucleus and ventral striatum modulated the tendency to be actively engaged in a behavior if the active ...
by the probabilistic reward task, and separately by EMA in the everyday life. ...
doi:10.1016/j.biopsycho.2017.04.014
pmid:28461214
fatcat:olt2jlbp2vaopfo7yqqsuxkox4
Extracting data from human manipulation of objects towards improving autonomous robotic grasping
2012
Robotics and Autonomous Systems
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This will enable modelling a class of tasks from sets of repeated demonstrations of the same task, so that a generalised probabilistic representation is derived to be used for task planning in artificial ...
In this work, we study how humans manipulate simple daily objects, and construct a probabilistic representation model for the tasks and objects useful for autonomous grasping and manipulation by robotic ...
The NotActive, LowActive and HighActive define the level of activation of that region during the in-hand manipulation task. ...
doi:10.1016/j.robot.2011.07.020
fatcat:nlnage3pefamnmry4hqwgdl23q
Probabilistic brains: knowns and unknowns
2013
Nature Neuroscience
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To date, however, these theories have only been applied to very simple tasks. ...
Probabilistic inference for multisensory integration Multisensory integration provides one of the best illustrations of the power of the probabilistic approach. ...
For instance, the activity of neurons in V1 is typically interpreted as encoding orientation, whereas neurons in area MT are thought to encode direction of motion. ...
doi:10.1038/nn.3495
pmid:23955561
pmcid:PMC4487650
fatcat:creg65nvmbhm3pprupmwc2c33a
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