Texture and Color Visual Features Based CBIR Using 2D DT-CWT and Histograms

2018 ◽  
pp. 84-96 ◽  
Author(s):  
Jitesh Pradhan ◽  
Sumit Kumar ◽  
Arup Kumar Pal ◽  
Haider Banka
Keyword(s):  
Visual Features

Reduced change blindness for task-relevant visual features during a social interaction

2001 ◽  
Author(s):  
Donald A. Varakin ◽  
Sheena Rogers ◽  
Jeffrey T. Andre ◽  
Susan L. Davis
Keyword(s):  
Social Interaction ◽  
Change Blindness ◽  
Visual Features

Using Convolutional Neural Networks to measure the contribution of visual features to the representation of object animacy in the brain

2019 ◽  
Author(s):  
Sushrut Thorat
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Temporal Cortex ◽  
Large Degree ◽  
Visual Features ◽  
Visual Feature ◽  
Visual Stream ◽  
Feature Information ◽  
Ventral Visual Stream ◽  
Animal Images

A mediolateral gradation in neural responses for images spanning animals to artificial objects is observed in the ventral temporal cortex (VTC). Which information streams drive this organisation is an ongoing debate. Recently, in Proklova et al. (2016), the visual shape and category (“animacy”) dimensions in a set of stimuli were dissociated using a behavioural measure of visual feature information. fMRI responses revealed a neural cluster (extra-visual animacy cluster - xVAC) which encoded category information unexplained by visual feature information, suggesting extra-visual contributions to the organisation in the ventral visual stream. We reassess these findings using Convolutional Neural Networks (CNNs) as models for the ventral visual stream. The visual features developed in the CNN layers can categorise the shape-matched stimuli from Proklova et al. (2016) in contrast to the behavioural measures used in the study. The category organisations in xVAC and VTC are explained to a large degree by the CNN visual feature differences, casting doubt over the suggestion that visual feature differences cannot account for the animacy organisation. To inform the debate further, we designed a set of stimuli with animal images to dissociate the animacy organisation driven by the CNN visual features from the degree of familiarity and agency (thoughtfulness and feelings). Preliminary results from a new fMRI experiment designed to understand the contribution of these non-visual features are presented.

Working Memory for Low-Level Visual Features: Mechanisms for Detecting the Mismatch between the Current and Stored in Memory Orientation

2018 ◽  
Vol 482 (2) ◽  
pp. 224-227
Author(s):  
E. Mikhaylova ◽  
◽  
N. Gerasimenko ◽  
P. Prokudin ◽  
◽  
...  
Keyword(s):  
Working Memory ◽  
Visual Features ◽  
Low Level

Construction of Visual Features of Indonesian Digital Poetry

2017 ◽  
Vol 3 (5) ◽  
pp. 1
Author(s):  
Johan Mahyudi ◽  
Djoko Saryono ◽  
Wahyudi Siswanto ◽  
Yuni Pratiwi
Keyword(s):  
Computer Technology ◽  
Visual Art ◽  
Feature Space ◽  
Digital Art ◽  
Visual Features ◽  
Technology Application ◽  
Digital Poetry ◽  
Textual Space ◽  
Neutral Space ◽  
Short Time

In short time, Indonesian digital poetry attracts its audience through a series of visualization features of the digital art. This research uses a short segment analysis on Indonesian videography digital poetry to demonstrate the existence of visual conglomeration practices through the creation of objects, features, a feature of space, measuring distance in feature space, and dimension reduction. These five approaches are proposed by Manovich (2014) in ​​grouping millions of visual artworks based on simple criteria. Of the three common objects are found, Indonesian animators, prefer individuals and texts as the main impression. The movement features are found in cinematic poetry and its rely depend on kinetic texts. Meanwhile, non-movement features can be found in the form of human imitation or part of them, portraits, silhouettes, and comics. Indonesian digital poetry of space features in form of textual space is prioritizing on the kinetics text, the space of time is prioritizing the presentation of objects association of words are spoken, the neutral space is prioritizing the use of computer technology application. The grouping of visual art composition is based on two criteria: the technique of creating and artistic impressions. The dimensional reducing is prominently practiced by Afrizal Malna.

Topography of Visual Features in the Human Ventral Visual Pathway

2021 ◽  
Author(s):  
Shijia Fan ◽  
Xiaosha Wang ◽  
Xiaoying Wang ◽  
Tao Wei ◽  
Yanchao Bi
Keyword(s):  
Visual Pathway ◽  
Visual Features ◽  
Ventral Visual Pathway

scholarly journals Evaluation of Multimodal External Human–Machine Interface for Driverless Vehicles in Virtual Reality

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 687
Author(s):  
Jinzhen Dou ◽  
Shanguang Chen ◽  
Zhi Tang ◽  
Chang Xu ◽  
Chengqi Xue
Keyword(s):  
New Technology ◽  
Pedestrian Safety ◽  
Human Machine Interface ◽  
Visual Features ◽  
Visual Modality ◽  
Human Voice ◽  
Road Users ◽  
Machine Interface ◽  
Interaction Efficiency ◽  
Physical Features

With the development and promotion of driverless technology, researchers are focusing on designing varied types of external interfaces to induce trust in road users towards this new technology. In this paper, we investigated the effectiveness of a multimodal external human–machine interface (eHMI) for driverless vehicles in virtual environment, focusing on a two-way road scenario. Three phases of identifying, decelerating, and parking were taken into account in the driverless vehicles to pedestrian interaction process. Twelve eHMIs are proposed, which consist of three visual features (smile, arrow and none), three audible features (human voice, warning sound and none) and two physical features (yielding and not yielding). We conducted a study to gain a more efficient and safer eHMI for driverless vehicles when they interact with pedestrians. Based on study outcomes, in the case of yielding, the interaction efficiency and pedestrian safety in multimodal eHMI design was satisfactory compared to the single-modal system. The visual modality in the eHMI of driverless vehicles has the greatest impact on pedestrian safety. In addition, the “arrow” was more intuitive to identify than the “smile” in terms of visual modality.

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