Person identification through entropy oriented mean shift clustering of human gaze patterns

Vella, Filippo; Infantino, Ignazio; Scardino, Giuseppe

doi:10.1007/s11042-015-3153-9

Cited by 13 publications

(17 citation statements)

References 20 publications

(34 reference statements)

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“…In identification scenarios, the more users the system has, the more realistic and more difficult the problem is, and thus, the performance of the system heavily depends on the sample size, the classification models, the device capabilities, and the required resources. Several surveyed works (52) focus on identification (e.g., [13,21,26,30,55,65,114,115,132,139,163]) while relatively less (21) focus on verification (e.g., [4,22,56,61,149,173]), which requires significantly less processing effort.…”

Section: Context Of Use and Design Perspectives Identification Vs Vermentioning

confidence: 99%

“…In contrast, when users authenticate through continuous stimuli, they may not be aware that they are being authenticated, as the stimuli are embedded to everyday tasks, such as reading emails and web browsing [38,163,172]. While continuous visual stimuli are of major importance for HCI as they enable unobtrusive authentication, they typically present lower accuracy and it is under-researched field, in comparison to controlled visual stimuli.…”

Section: Continuous Vs Controlled Visual Stimulimentioning

confidence: 99%

See 1 more Smart Citation

The Role of Eye Gaze in Security and Privacy Applications: Survey and Future HCI Research Directions

Katsini¹,

Abdrabou

Raptis³

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

116

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For the past 20 years, researchers have investigated the use of eye tracking in security applications. We present a holistic view on gaze-based security applications. In particular, we canvassed the literature and classify the utility of gaze in security applications into a) authentication, b) privacy protection, and c) gaze monitoring during security critical tasks. This allows us to chart several research directions, most importantly 1) conducting field studies of implicit and explicit gaze-based authentication due to recent advances in eye tracking, 2) research on gaze-based privacy protection and gaze monitoring in security critical tasks which are under-investigated yet very promising areas, and 3) understanding the privacy implications of pervasive eye tracking. We discuss the most promising opportunities and most pressing challenges of eye tracking for security that will shape research in gaze-based security applications for the next decade.

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Section: Context Of Use and Design Perspectives Identification Vs Vermentioning

confidence: 99%

Section: Continuous Vs Controlled Visual Stimulimentioning

confidence: 99%

The Role of Eye Gaze in Security and Privacy Applications: Survey and Future HCI Research Directions

Katsini¹,

Abdrabou

Raptis³

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

116

View full text Add to dashboard Cite

show abstract

“…Comaniciu et al [17] proposed a kernel-based object tracking method, where object region tracking is denoted using a spatially weighted intensity histogram, and its similarity rate is computed using Bhattacharyya distance following an iterative mean-shift technique. Many applications [18][19][20][21] later proposed various mean-shift algorithm variants. Even though the mean-shift object tracking technique is well-performed over sequences with comparatively slight object displacement, its performance cannot be guaranteed in the case where objects suffers full or partial occlusions.…”

Section: Related Workmentioning

confidence: 99%

“…The proposed algorithm of weighted resampling prevents this problem. First, the top sample is selected and set to S top t with N top weights from set S t , as shown in Equations (20) to (21). The parameter top represents the top rate and for our experiment it is set to 0.…”

Section: (C)mentioning

confidence: 99%

An Intelligent Automatic Human Detection and Tracking System Based on Weighted Resampling Particle Filtering

Chang

Pare

Meena

et al. 2020

BDCC

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At present, traditional visual-based surveillance systems are becoming impractical, inefficient, and time-consuming. Automation-based surveillance systems appeared to overcome these limitations. However, the automatic systems have some challenges such as occlusion and retaining images smoothly and continuously. This research proposes a weighted resampling particle filter approach for human tracking to handle these challenges. The primary functions of the proposed system are human detection, human monitoring, and camera control. We used the codebook matching algorithm to define the human region as a target and track it, and we used the practical filter algorithm to follow and extract the target information. Consequently, the obtained information was used to configure the camera control. The experiments were tested in various environments to prove the stability and performance of the proposed system based on the active camera.

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“…The pixel points which fulfill ( , ) + ( , ) > 0 are regarded as centers of clusters. We compared 3 different kinds of clustering algorithms: mean shift clustering [Vella, Infantino and Scardino (2017)], k-means clustering and AP clustering. The results of the three clustering algorithms are presented in Fig.…”

Section: =1mentioning

confidence: 99%

An Efficient Crossing-Line Crowd Counting Algorithm with Two-Stage Detection

Zhen-qiu¹,

Yang²,

Tjahjadi³

2019

Computers, Materials &Amp; Continua

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Crowd counting is a challenging task in crowded scenes due to heavy occlusions, appearance variations and perspective distortions. Current crowd counting methods typically operate on an image patch level with overlaps, then sum over the patches to get the final count. In this paper we describe a real-time pedestrian counting framework based on a two-stage human detection algorithm. Existing works with overhead cameras is mainly based on visual tracking, and their robustness is rather limited. On the other hand, some works, which focus on improving the performances, are too complicated to be realistic. By adopting a line sampling process, a temporal slice image can be obtained for pedestrian counting without the need for visual tracking. Only ten low level features are extracted from the input image to establish a feature vector. As a result, our algorithm is more efficient and accurate than existing methods. Pedestrians in the temporal slice image are then located by the two-stage detection algorithm, which is largely based on support vector machine and affinity propagation clustering. Moreover, a novel algorithm is proposed to determine the moving directions of pedestrians by comparing the centers of them in two temporal slice images. Extensive experiments reveal that our system achieves satisfaction performances in terms of both robustness and efficiency.

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Person identification through entropy oriented mean shift clustering of human gaze patterns

Cited by 13 publications

References 20 publications

The Role of Eye Gaze in Security and Privacy Applications: Survey and Future HCI Research Directions

The Role of Eye Gaze in Security and Privacy Applications: Survey and Future HCI Research Directions

An Intelligent Automatic Human Detection and Tracking System Based on Weighted Resampling Particle Filtering

An Efficient Crossing-Line Crowd Counting Algorithm with Two-Stage Detection

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