Alzheimer's Disease (AD) is a neurodegenerative disorder that causes continuous decline in cognitive functions and eventually results death. An early AD diagnosis important for taking active measures to slow its deterioration. Traditional diagnoses are usually based on clinical experience, which limited by several realistic factors. In this paper, we focus exploiting deep learning techniques diagnose eye-tracking behaviors. Visual attention, as typical behavior, of great value detecting...

Eye-tracking technology has become a powerful tool for biomedical-related applications due to its simplicity of operation and low requirements on patient language skills. This study aims use the machine-learning models deep-learning networks identify key features eye movements in Alzheimer's Disease (AD) under specific visual tasks, thereby facilitating computer-aided diagnosis AD. Firstly, three-dimensional (3D) visuospatial memory task is designed provide participants with stimuli while...

Alzheimer's disease (AD) is a degenerative neurological that occurs in the elderly with typical symptoms of decline cognition, manifested by eye movement behaviors. The key to AD treatment requires early detection cognitive impairment, which relies on frequent medical screening. This article proposes an Internet Things (IoT) architecture constructed eye-tracker (ET) nodes and cloud-based diagnosis enabled machine learning (ML), can provide convenient screening oculomotor abnormalities...

As a powerful global registration method for point clouds, the 4-points congruent sets (4PCS) algorithm has been wildly used in 3D scene reconstruction field. In this paper, we propose an adaptive 4PCS (A4PCS), which aims to provide robustness rigid transformation two or more overlapping laser scans. The proposed only incorporates distance information of stereoscopic base set and fast mechanism extraction into 4PCS. To ensure accuracy when dealing with restrictive situations, such as clouds...

Pedestrian navigation systems could serve as a good supplement for other methods or extending into areas where are invalid. Due to the accumulation of inertial sensing errors, foot-mounted inertial-sensor-based pedestrian (PNSs) suffer from drift, especially heading drift. To mitigate considering complexity human motion and environment, we introduce novel hybrid framework that integrates foot-state classifier triggers zero-velocity update (ZUPT) algorithm, zero-angular-rate (ZARU) state...

Eye-tracking technology is increasingly used in applications such as 3D displays and human-computer interaction (HCI). However, most current eye trackers focus on 2D point-of-gaze (PoG) estimation cannot provide accurate gaze depth. Concerning future HCI with displays, we propose an integrated binocular eye-tracking device stereo stimuli to highly PoG estimation. In our device, the imaging system can users a friendly immersive visual experience without wearing any accessories. The...

The live broadcasting of game playing is becoming more and popular. video one the typical data which should be coded with high efficiency coding-screen content coding (HEVC-SCC). In HEVC-SCC, palette mode an important technique can effectively enhance performance. However, this also demands high-coding computation. paper, we propose a fast pre-decision method based on analysis color complexity data. Considering only computation our algorithm saves about 74.24% in experiments videos. Whereas,...

Alzheimer's Disease (AD) causes a continuous decline in memory, thinking, and judgment. Traditional diagnoses are usually based on clinical experience, which is limited by some realistic factors. In this paper, we focus exploiting deep learning techniques to diagnose AD eye-tracking behaviors. Visual attention, as typical behavior, of great value detect cognitive abnormalities patients. To better analyze the differences visual attention between patients normals, first conduct 3D...

Eye-tracking technologies have been widely used in applications like psychological studies and human computer interactions (HCI). However, most current eye trackers focus on 2D point of gaze (PoG) estimation cannot provide accurate depth.Concerning future such as HCI with 3D displays, we propose a novel binocular tracking device stereo stimuli to highly PoG estimation. In our device, the imaging system can users friendly immersive visual experience without wearing any accessories. The...

With the increasing prevalence of 3D videos, understanding distinctions between 2D and video experiences has become significantly important. In our study, we explored cognitive load imposed by stimuli under various tasks using electroencephalogram (EEG) data. To assess load, introduced Cognitive Load Index (CLI), a measure that combines oscillations theta alpha oscillations. Our experimental setup included four stimuli, each associated with typical tasks. Participants were exposed to both...