MOTION ANALYSIS AND REPRESENTATION IN COMPUTER VISION

1993 ◽  
Vol 03 (04) ◽  
pp. 797-831 ◽  
Author(s):  
V. CAPPELLINI ◽  
A. MECOCCI ◽  
A. DEL BIMBO
Keyword(s):  
Computer Vision ◽  
Motion Analysis ◽  
Image Sequences ◽  
Motion Field ◽  
Short Term ◽  
High Interest ◽  
Motion Parameters ◽  
Qualitative Estimation

Motion analysis is of high interest in many different fields for a number of crucial applications. Short-term motion analysis addresses the computation of motion parameters or the qualitative estimation of the motion field. Long-term motion analysis aims at the understanding of motion and includes reasoning on motion properties. Image sequences are in general processed to perform the above motion analysis. These subjects are considered in this review with reference to the more significant results in the literature both at theory and application levels.

A Canonical Microfunction for Learning Perceptual Invariances

Perception ◽  
1996 ◽  
Vol 25 (2) ◽  
pp. 207-220 ◽  
Author(s):  
James V Stone
Keyword(s):  
Model Neuron ◽  
Learning Rule ◽  
Image Sequences ◽  
Weight Changes ◽  
Short Term ◽  
Stereo Disparity ◽  
Random Dot Stereograms ◽  
Long Time ◽  
Generic Strategy

An unsupervised method is presented which permits a set of model neurons, or a microcircuit, to learn low-level vision tasks, such as the extraction of surface depth. Each microcircuit implements a simple, generic strategy which is based on a key assumption: perceptually salient visual invariances, such as surface depth, vary smoothly over time. In the process of learning to extract smoothly varying invariances, each microcircuit maximises a microfunction. This is achieved by means of a learning rule which maximises the long-term variance of the state of a model neuron and simultaneously minimises its short-term variance. The learning rule involves a linear combination of anti-Hebbian and Hebbian weight changes, over short and long time scales, respectively. The method is demonstrated on a hyperacuity task: estimating subpixel stereo disparity from a temporal sequence of random-dot stereograms. After learning, the microcircuit generalises, without additional learning, to previously unseen image sequences. It is proposed that the approach adopted here may be used to define a canonical microfunction, which can be used to learn many perceptually salient invariances.

scholarly journals Integral Model for Distributing Functional Roles Within a Working Team

2014 ◽  
Vol 9 (1-2) ◽  
Author(s):  
Beti Andonovic ◽  
Marina Spasovska ◽  
Mishela Temkov ◽  
Aleksandar Dimitrov
Keyword(s):  
Integral Model ◽  
Short Term ◽  
Team Members ◽  
Functional Roles ◽  
High Interest ◽  
Efficiency And Effectiveness ◽  
Original Approach

Abstract: Long-term and short-term efficiency and effectiveness of a working team depend on an optimal Roles distribution within it. Therefore, having a model which enables such corresponding distribution is of a high interest to any quality manager. Two main concepts, the Roles concept of Adizes and Working styles concept of Julie Hay, are involved to create an integral model with an original approach to the Roles distribution in any working team. The greatest advantage of this model is that it is predictive instead of experiential: it makes it possible to make a corresponding Roles distribution in advance within the team, without previously monitoring the activities of the potential team members. A discussion to the relation between the possible outcomes and the level of prediction is given.

Learning Perceptually Salient Visual Parameters Using Spatiotemporal Smoothness Constraints

1996 ◽  
Vol 8 (7) ◽  
pp. 1463-1492 ◽  
Author(s):  
James V. Stone
Keyword(s):  
Low Frequency ◽  
Learning Rule ◽  
Input Sequence ◽  
Image Sequences ◽  
Weight Changes ◽  
Short Term ◽  
Long Time ◽  
Temporal Sequences ◽  
Perceptual Systems

A model is presented for unsupervised learning of low level vision tasks, such as the extraction of surface depth. A key assumption is that perceptually salient visual parameters (e.g., surface depth) vary smoothly over time. This assumption is used to derive a learning rule that maximizes the long-term variance of each unit's outputs, whilst simultaneously minimizing its short-term variance. The length of the half-life associated with each of these variances is not critical to the success of the algorithm. The learning rule involves a linear combination of anti-Hebbian and Hebbian weight changes, over short and long time scales, respectively. This maximizes the information throughput with respect to low-frequency parameters implicit in the input sequence. The model is used to learn stereo disparity from temporal sequences of random-dot and gray-level stereograms containing synthetically generated subpixel disparities. The presence of temporal discontinuities in disparity does not prevent learning or generalization to previously unseen image sequences. The implications of this class of unsupervised methods for learning in perceptual systems are discussed.

Greek coalition will play politics at debt talks

2016 ◽  
Keyword(s):  
Debt Relief ◽  
Short Term ◽  
Trade Off ◽  
Content Type ◽  
High Interest ◽  
Political Position ◽  
The Government ◽  
Opinion Polls ◽  
Staff Level

Significance The government, with half an eye on a snap election, is determined not to accede to prolonged austerity without the trade-off of significant debt relief. Timing is all. The coalition partners are faring badly in opinion polls but do not face high-interest debt repayments before mid-2017, allowing them to prolong negotiations while they try to improve their political position. Impacts The government and Greece’s creditors are deeply divided over how long primary surpluses must be maintained and how to use them. Greece has been given limited short-term debt relief through adjustments to repayment conditions. There are no commitments regarding medium- or long-term measures and no haircut on the country’s mountainous aggregate debt. The IMF will rejoin the bailout once there is a staff-level agreement but insists that the numbers must add up.

scholarly journals Comparative Study of Relative-Pose Estimations from a Monocular Image Sequence in Computer Vision and Photogrammetry

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1905 ◽  
Author(s):  
Tserennadmid Tumurbaatar ◽  
Taejung Kim
Keyword(s):  
Computer Vision ◽  
Image Sequences ◽  
Consumer Electronics ◽  
Estimation Methods ◽  
Single Camera ◽  
Essential Matrix ◽  
3D Motion ◽  
Monocular Image ◽  
Motion Parameters ◽  
Relative Pose

Techniques for measuring the position and orientation of an object from corresponding images are based on the principles of epipolar geometry in the computer vision and photogrammetric fields. Contributing to their importance, many different approaches have been developed in computer vision, increasing the automation of the pure photogrammetric processes. The aim of this paper is to evaluate the main differences between photogrammetric and computer vision approaches for the pose estimation of an object from image sequences, and how these have to be considered in the choice of processing technique when using a single camera. The use of a single camera in consumer electronics has enormously increased, even though most 3D user interfaces require additional devices to sense 3D motion for their input. In this regard, using a monocular camera to determine 3D motion is unique. However, we argue that relative pose estimations from monocular image sequences have not been studied thoroughly by comparing both photogrammetry and computer vision methods. To estimate motion parameters characterized by 3D rotation and 3D translations, estimation methods developed in the computer vision and photogrammetric fields are implemented. This paper describes a mathematical motion model for the proposed approaches, by differentiating their geometric properties and estimations of the motion parameters. A precision analysis is conducted to investigate the main characteristics of the methods in both fields. The results of the comparison indicate the differences between the estimations in both fields, in terms of accuracy and the test dataset. We show that homography-based approaches are more accurate than essential-matrix or relative orientation–based approaches under noisy conditions.

scholarly journals Dynamic Codebook for Foreground Segmentation in a Video

2017 ◽  
Vol 10 (2) ◽  
pp. 144-155
Author(s):  
Worapan Kusakunniran ◽  
Rawitas Krungkaew
Keyword(s):  
Computer Vision ◽  
Real World ◽  
Early Stage ◽  
Image Sequences ◽  
Foreground Segmentation ◽  
Background Information ◽  
Detection Algorithms ◽  
Change Detection Algorithms ◽  
Novel Method

The foreground segmentation in a video is a way to extract changes in image sequences. It is a key task in an early stage of many applications in the computer vision area. The information of changes in the scene must be segmented before any further analysis could be taken place. However, it remains with difficulties caused by several real-world challenges such as cluttered backgrounds, changes of the illumination, shadows, and long-term scene changes. This paper proposes a novel method, namely a dynamic codebook (DCB), to address such challenges of the dynamic backgrounds. It relies on a dynamic modeling of the background scene. Initially, a codebook is constructed to represent the background information of each pixel over a period of time. Then, a dynamic boundary of the codebook will be made to support variations of the background. The revised codebook will always be adaptive to the new background's environments. This makes the foreground segmentation more robust to the changes of background scene. The proposed method has been evaluated by using the changedetection.net (CDnet) benchmark which is a well-known video dataset for testing change-detection algorithms. The experimental results and comprehensive comparisons have shown a very promising performance of the proposed method.

Conceptual short-term memory (CSTM) supports core claims of Christiansen and Chater

2016 ◽  
Vol 39 ◽  
Author(s):  
Mary C. Potter
Keyword(s):  
Working Memory ◽  
Rapid Serial Visual Presentation ◽  
Language Comprehension ◽  
Short Term Memory ◽  
Visual Presentation ◽  
Long Term Memory ◽  
Short Term ◽  
Term Memory ◽  
Use Of Knowledge

AbstractRapid serial visual presentation (RSVP) of words or pictured scenes provides evidence for a large-capacity conceptual short-term memory (CSTM) that momentarily provides rich associated material from long-term memory, permitting rapid chunking (Potter 1993; 2009; 2012). In perception of scenes as well as language comprehension, we make use of knowledge that briefly exceeds the supposed limits of working memory.

Ultrastructural investigations of MDL 19,660-induced effects on the canine platelet and megakaryocyte

1990 ◽  
Vol 48 (3) ◽  
pp. 374-375
Author(s):  
D.E. Loudy ◽  
J. Sprinkle-Cavallo ◽  
J.T. Yarrington ◽  
F.Y. Thompson ◽  
J.P. Gibson
Keyword(s):  
Antidepressant Drug ◽  
Beagle Dogs ◽  
Long Term Effects ◽  
Short Term ◽  
Platelet Counts ◽  
Toxicological Studies ◽  
Induced Aggregation ◽  
Internal Architecture

Previous short term toxicological studies of one to two weeks duration have demonstrated that MDL 19,660 (5-(4-chlorophenyl)-2,4-dihydro-2,4-dimethyl-3Hl, 2,4-triazole-3-thione), an antidepressant drug, causes a dose-related thrombocytopenia in dogs. Platelet counts started to decline after two days of dosing with 30 mg/kg/day and continued to decrease to their lowest levels by 5-7 days. The loss in platelets was primarily of the small discoid subpopulation. In vitro studies have also indicated that MDL 19,660: does not spontaneously aggregate canine platelets and has moderate antiaggregating properties by inhibiting ADP-induced aggregation. The objectives of the present investigation of MDL 19,660 were to evaluate ultrastructurally long term effects on platelet internal architecture and changes in subpopulations of platelets and megakaryocytes.Nine male and nine female beagle dogs were divided equally into three groups and were administered orally 0, 15, or 30 mg/kg/day of MDL 19,660 for three months. Compared to a control platelet range of 353,000- 452,000/μl, a doserelated thrombocytopenia reached a maximum severity of an average of 135,000/μl for the 15 mg/kg/day dogs after two weeks and 81,000/μl for the 30 mg/kg/day dogs after one week.

Comparison of Auditory, Language, Memory, and Attention Abilities in Children With and Without Listening Difficulties

2020 ◽  
Vol 29 (4) ◽  
pp. 710-727
Author(s):  
Beula M. Magimairaj ◽  
Naveen K. Nagaraj ◽  
Alexander V. Sergeev ◽  
Natalie J. Benafield
Keyword(s):  
Auditory Processing ◽  
Short Term Memory ◽  
Group Differences ◽  
Long Term Memory ◽  
Short Term ◽  
Significant Group ◽  
Term Memory ◽  
Memory And Attention ◽  
Speed And Accuracy

Objectives School-age children with and without parent-reported listening difficulties (LiD) were compared on auditory processing, language, memory, and attention abilities. The objective was to extend what is known so far in the literature about children with LiD by using multiple measures and selective novel measures across the above areas. Design Twenty-six children who were reported by their parents as having LiD and 26 age-matched typically developing children completed clinical tests of auditory processing and multiple measures of language, attention, and memory. All children had normal-range pure-tone hearing thresholds bilaterally. Group differences were examined. Results In addition to significantly poorer speech-perception-in-noise scores, children with LiD had reduced speed and accuracy of word retrieval from long-term memory, poorer short-term memory, sentence recall, and inferencing ability. Statistically significant group differences were of moderate effect size; however, standard test scores of children with LiD were not clinically poor. No statistically significant group differences were observed in attention, working memory capacity, vocabulary, and nonverbal IQ. Conclusions Mild signal-to-noise ratio loss, as reflected by the group mean of children with LiD, supported the children's functional listening problems. In addition, children's relative weakness in select areas of language performance, short-term memory, and long-term memory lexical retrieval speed and accuracy added to previous research on evidence-based areas that need to be evaluated in children with LiD who almost always have heterogenous profiles. Importantly, the functional difficulties faced by children with LiD in relation to their test results indicated, to some extent, that commonly used assessments may not be adequately capturing the children's listening challenges. Supplemental Material https://doi.org/10.23641/asha.12808607

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