scholarly journals A two-level computer vision-based information processing method for improving the performance of human–machine interaction-aided applications

2020 ◽  
Author(s):  
Osama Alfarraj ◽  
Amr Tolba
Keyword(s):  
Computer Vision ◽  
Information Processing ◽  
Visual Information ◽  
Information Gain ◽  
Processing System ◽  
Human Machine Interaction ◽  
Visual Inputs ◽  
Level Data ◽  
Processing Errors ◽  
Fully Connected

Abstract The computer vision (CV) paradigm is introduced to improve the computational and processing system efficiencies through visual inputs. These visual inputs are processed using sophisticated techniques for improving the reliability of human–machine interactions (HMIs). The processing of visual inputs requires multi-level data computations for achieving application-specific reliability. Therefore, in this paper, a two-level visual information processing (2LVIP) method is introduced to meet the reliability requirements of HMI applications. The 2LVIP method is used for handling both structured and unstructured data through classification learning to extract the maximum gain from the inputs. The introduced method identifies the gain-related features on its first level and optimizes the features to improve information gain. In the second level, the error is reduced through a regression process to stabilize the precision to meet the HMI application demands. The two levels are interoperable and fully connected to achieve better gain and precision through the reduction in information processing errors. The analysis results show that the proposed method achieves 9.42% higher information gain and a 6.51% smaller error under different classification instances compared with conventional methods.

Visual Hallucinations and Impaired Conscious Visual Perception in Parkinson Disease

2019 ◽  
Vol 33 (6) ◽  
pp. 377-385 ◽  
Author(s):  
Akira Kurita ◽  
Hiroaki Koshikawa ◽  
Takeshi Akiba ◽  
Kanako Seki ◽  
Hiroaki Ishikawa ◽  
...  
Keyword(s):  
Information Processing ◽  
Parkinson Disease ◽  
Basal Forebrain ◽  
Visual Information ◽  
Striate Cortex ◽  
Processing System ◽  
Auditory Hallucinations ◽  
Pathophysiological Mechanism ◽  
Visual Hallucinations ◽  
Parietal Cortices

Visual hallucinations (VHs) are common in patients with Parkinson disease (PD), especially those with dementia, whereas auditory hallucinations are quite rare. Recent studies have revealed the involvement of several regions along the visual information-processing system that contribute to the pathophysiological mechanism of VHs: the eyes and retina, retinofugal projection, lateral geniculate nucleus, striate cortex, ventral pathways in the temporal cortices, and frontal and parietal cortices. In addition, the concurrent involvement of other systems in the brainstem and basal forebrain further modify VHs in PD. In this review, we discuss the pathophysiological association between the regional involvement of these areas and VHs.

Do the TAIS Attentional-Style Scales Predict How Visual Information Is Processed?

1989 ◽  
Vol 11 (2) ◽  
pp. 171-186 ◽  
Author(s):  
Deborah Dewey ◽  
Lawrence R. Brawley
Keyword(s):  
Information Processing ◽  
Visual Search ◽  
Visual Information ◽  
Search Time ◽  
Processing System ◽  
Integration Theory ◽  
Future Research ◽  
Search Rate ◽  
Information Processing System ◽  
Attentional Style

A major research limitation in investigating the validity of the TAIS has been the failure to distinguish when attentional style has an effect on the information processing system, early as in encoding or late after processing. Few investigations have examined the TAIS predictive validity in a controlled setting wherein task attention demands can be systematically and accurately varied. Does the general trait of attentional style really have anything to do with how attention related information is processed? The present study examined this question using a valid attention theory (Treisman's feature integration theory) and a visual search paradigm. When the TAIS attentional-style scales were correlated with visual search rate for attention demanding targets, no significant relationships were observed. Specifically, TAIS scales did not relate to visual search rate for an attention demanding target, the performance of subjects extreme in search rate, or the central to peripheral slowing of search time in target detection. The factorial validity of the TAIS was also questioned. It was concluded that the attentional-style scales were not valid in predicting how attention related visual information is processed. The importance of distinguishing when attentional style might be operating in the information processing system was emphasized for future research.

Information Processing Based on SQLite for Target Tracking System

2013 ◽  
Vol 278-280 ◽  
pp. 2065-2068
Author(s):  
Jun Lin Liu ◽  
Qi Yuan Sun
Keyword(s):  
Information Processing ◽  
Visual Information ◽  
System Analysis ◽  
Tracking System ◽  
Processing System ◽  
Analysis Data ◽  
Visual Surveillance ◽  
Hardware Platform ◽  
Data Objects ◽  
Sqlite Database

As for the digital visual surveillance system, the traditional database and hardware platform can not be good at processing vast quantities of information. Combined with ActiveX Data Objects (ADO) technology, the information processing system was built by using SQLite database with embedded dual-core platform. The embedded database SQLite is implanted in the existing embedded hardware platform DM6446. And processing modules and operating interface were designed based on SQLite and the embedded hardware platform. The designed system can play a role as the core of data processing. The experiments show that the system can meet the requirements of the visual information processing such as data mining, online system analysis, data post-processing and so on.

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