A simple translation in cortical log-coordinates may account for the pattern of saccadic localization errors

2004 ◽  
Vol 91 (3) ◽  
Author(s):  
Rufin VanRullen
Keyword(s):  
Localization Errors ◽  
Saccadic Localization

Perception of Visual Space at the Time of Pro- and Anti-Saccades

2004 ◽  
Vol 91 (6) ◽  
pp. 2457-2464 ◽  
Author(s):  
Holger Awater ◽  
Markus Lappe
Keyword(s):  
Eye Movement ◽  
Visual Space ◽  
Saccade Target ◽  
Complete Darkness ◽  
Visual Cue ◽  
Localization Errors ◽  
Mouse Pointer ◽  
Saccade Direction ◽  
Anti Saccades ◽  
Saccadic Localization

The localization of peri-saccadically flashed objects shows two types of errors: first, a uniform shift in saccade direction, and second, a compression of visual space around the saccade target. Whereas the uniform shift occurs when the experiment is performed in complete darkness compression occurs when additional visual references are available. Thus peri-saccadic mislocalization contains motor and visual components. To distinguish between both factors we compared peri-saccadic localization errors during pro- and anti-saccades. In the case of anti-saccades, the visual cue that elicits the saccade and the actual eye movement are in opposite directions. We asked whether peri-saccadic compression can be observed with anti-saccades, and if so, whether the compression is directed toward the visual cue or follows the actual eye movement. In blocked trials, subjects performed saccades either toward a visual cue (pro-saccade) or to the mirrored position opposite to a visual cue (anti-saccade). Peri-saccadically, we flashed a thin vertical bar at one of four possible locations. Subjects had to indicate the perceived position of the bar with a mouse pointer about 500 ms after the saccade. Experiments were performed in complete darkness and with visual references. Peri-saccadic mislocalizations occurred during anti-saccades. The mislocalizations were very similar for pro- and anti-saccades in magnitude and direction. For both, pro- and anti-saccades, mislocalizations were directed toward the actual eye movement and not the visual cue.

scholarly journals Analysis of Occlusion Effects for Map-Based Self-Localization in Urban Areas

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5196
Author(s):  
Yuki Endo ◽  
Ehsan Javanmardi ◽  
Shunsuke Kamijo
Keyword(s):  
Urban Areas ◽  
Structural Information ◽  
Average Error ◽  
High Definition ◽  
Geometrical Structures ◽  
Real Environment ◽  
Surrounding Environment ◽  
Localization Errors ◽  
Stable Estimation ◽  
High Level

A high-definition (HD) map provides structural information for map-based self-localization, enabling stable estimation in real environments. In urban areas, there are many obstacles, such as buses, that occlude sensor observations, resulting in self-localization errors. However, most of the existing HD map-based self-localization evaluations do not consider sudden significant errors due to obstacles. Instead, they evaluate this in terms of average error over estimated trajectories in an environment with few occlusions. This study evaluated the effects of self-localization estimation on occlusion with synthetically generated obstacles in a real environment. Various patterns of synthetic occlusion enabled the analyses of the effects of self-localization error from various angles. Our experiments showed various characteristics that locations susceptible to obstacles have. For example, we found that occlusion in intersections tends to increase self-localization errors. In addition, we analyzed the geometrical structures of a surrounding environment in high-level error cases and low-level error cases with occlusions. As a result, we suggested the concept that the real environment should have to achieve robust self-localization under occlusion conditions.

scholarly journals Orientation-Constrained System for Lamp Detection in Buildings Based on Computer Vision

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1516 ◽  
Author(s):  
Francisco Troncoso-Pastoriza ◽  
Pablo Eguía-Oller ◽  
Rebeca Díaz-Redondo ◽  
Enrique Granada-Álvarez ◽  
Aitor Erkoreka
Keyword(s):  
Computer Vision ◽  
Optimization Methods ◽  
Geometric Information ◽  
Constrained System ◽  
Building Information Modelling ◽  
Correct Model ◽  
Reprojection Error ◽  
Localization Errors ◽  
Building Information ◽  
Error Filtering

Computer vision is used in this work to detect lighting elements in buildings with the goal of improving the accuracy of previous methods to provide a precise inventory of the location and state of lamps. Using the framework developed in our previous works, we introduce two new modifications to enhance the system: first, a constraint on the orientation of the detected poses in the optimization methods for both the initial and the refined estimates based on the geometric information of the building information modelling (BIM) model; second, an additional reprojection error filtering step to discard the erroneous poses introduced with the orientation restrictions, keeping the identification and localization errors low while greatly increasing the number of detections. These enhancements are tested in five different case studies with more than 30,000 images, with results showing improvements in the number of detections, the percentage of correct model and state identifications, and the distance between detections and reference positions.

Analysis of localization errors in the definition of the mantle field using a beam's eye view treatment-planning system

1996 ◽  
Vol 35 (2) ◽  
pp. 377-382 ◽  
Author(s):  
John D. Naida ◽  
Avraham Eisbruch ◽  
Sonja L. Schoeppel ◽  
Howard M. Sandler ◽  
Andrew T. Turrisi ◽  
...  
Keyword(s):  
Treatment Planning ◽  
Planning System ◽  
Treatment Planning System ◽  
Localization Errors ◽  
Definition Of

New Leak Location Approaches for Gas Pipelines Using Acoustic Waves

2018 ◽  
Author(s):  
Cuiwei Liu ◽  
Yuxing Li ◽  
Qihui Hu ◽  
Wuchang Wang ◽  
Yazhen Wang ◽  
...  
Keyword(s):  
Natural Gas ◽  
Acoustic Waves ◽  
Economic Loss ◽  
Transportation Systems ◽  
Gas Pipelines ◽  
Natural Gas Pipelines ◽  
New Methods ◽  
Leak Location ◽  
Localization Errors ◽  
Leak Localization

Natural gas is a vital energy carrier which can serve as an energy source, which is extremely vulnerable to leakages from pipeline transportation systems. The required ignition energy is low. Although the safety of natural gas pipelines has been improved, the average economic loss of natural gas accidents, including leaks, is large. To solve these problems, an acoustic leak localization system is designed and researched for gas pipelines using experiments with methods proposed according to different application situations. The traditional method with two sensors installed at both ends can be improved by a newly proposed combined signal-processing method, which is applied for the case that it is necessary to calculate the time differences with data synchronicity. When the time differences cannot be calculated accurately, a new method based on the amplitude attenuation model is proposed. Using these methods, the system can be applied to most situations. Next, an experimental facility at the laboratory scale is established, and experiments are carried out. Finally, the methods are verified and applied for leak localization. The results show that this research can provide a foundation for the proposed methods. The maximum experimental leak localization errors for the methods are −0.592%, and −7.62%. It is concluded that the system with the new methods can be applied to protect and monitor natural gas pipelines.

scholarly journals Overcoming Localization Errors due to Node Power Drooping in a Wireless Sensor Network

2011 ◽  
Vol 57 (3) ◽  
pp. 341-346 ◽  
Author(s):  
Safdar Khan ◽  
Boubaker Daachi ◽  
Karim Djouani
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Vital Role ◽  
Position Estimation ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Voltage ◽  
Localization Errors ◽  
Anchor Nodes ◽  
Received Signal Strength Indication

Overcoming Localization Errors due to Node Power Drooping in a Wireless Sensor NetworkReceived Signal Strength Indication (RSSI) plays a vital role in the range-free localization of sensor nodes in a wireless sensor network and a good amount of research has been made in this regard. One important factor is the battery voltage of the nodes (i.e., the MICAz sensors) which is not taken into account in the existing literature. As battery voltage level performs an indispensable role for the position estimation of sensor nodes through anchor nodes therefore, in this paper, we take into a account this crucial factor and propose an algorithm that overcomes the problem of decaying battery. We show the results, in terms of more precise localization of sensor nodes through simulation. This work is an extension to [1] and now we also use neural network to overcome the localization errors generated due to gradual battery voltage drooping.

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