Eyecam: Revealing Relations between Humans and Sensing Devices through an Anthropomorphic Webcam

Teyssier, Marc; Koelle, Marion; Strohmeier, Paul; Fruchard, Bruno; Steimle, Jürgen

doi:10.1145/3411764.3445491

Cited by 15 publications

(10 citation statements)

References 96 publications

(85 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It can be realized by verbal information from the host [31,50], or by notifications that guests receive on personal devices [13,51]. Another measure is given by status or location indicators [1,32,44,45,50,51]. Yao et al suggest labeling IoT devices with QR-codes that link to privacy information [49].…”

Section: Guest Privacy Mechanismsmentioning

confidence: 99%

“You offer privacy like you offer tea”: Investigating Mechanisms for Improving Guest Privacy in IoT-Equipped Households

Marky

Gerber

Pelzer

et al. 2022

PoPETs

View full text Add to dashboard Cite

IoT devices are becoming more common and prevalent in private households. Since guests can be present in IoT-equipped households, IoT devices can pose considerable privacy risks to them. In this paper, we present an in-depth evaluation of privacy protection for guests considering the perspectives of hosts and guests. First, we interviewed 21 IoT device owners about four classes of mechanisms obtained from the literature and social aspects. Second, we conducted an online survey (N=264) that investigates the perspective of guests in IoT-equipped households. From our results, we learn that protection mechanisms should not introduce privacy threats and require low resources. Further, hosts should keep control over their devices and the aesthetics of their living spaces. Guests, however, value feedback about the status of privacy protection which can interfere with aesthetics. Privacy protection should rather foster collaboration and not impact the visit of the guest too severely. We use our results to identify a design space for guest privacy protection in IoT-equipped households.

show abstract

Section: Guest Privacy Mechanismsmentioning

confidence: 99%

“You offer privacy like you offer tea”: Investigating Mechanisms for Improving Guest Privacy in IoT-Equipped Households

Marky

Gerber

Pelzer

et al. 2022

PoPETs

View full text Add to dashboard Cite

show abstract

“…• Device Status such as color indicator LEDs conveying device on/o state and basic activity [9,147] • Mode transparency through privacy labels [88,89], conveying information regarding intent and activity through iconographic, textual, and color-coded displays [73] • Scope and activity using on-device displays to convey detail regarding capture area and eld of view [73] or intent (e.g. EyeCam [150]), toward full presentations of activity such as MirrorCam [72].…”

Section: Bystander / Extrinsicmentioning

confidence: 99%

“…Building on this, MirrorCam [72] explored a wearable camera with an in-built mirror display to support bystander situational awareness regarding who was in-view, and whether the camera was on/o . And Eyecam [150] utilized an anthropomorphic webcam to establish a di erent form of relationship between the sensor and those being observed, in particular enabling the sensor to embody/convey agency and intent.…”

Section: Awareness and Activity Transparencymentioning

confidence: 99%

Privacy-Enhancing Technology and Everyday Augmented Reality

O’Hagan

Saeghe

Gugenheimer

et al. 2022

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

View full text Add to dashboard Cite

Fundamental to Augmented Reality (AR) headsets is their capacity to visually and aurally sense the world around them, necessary to drive the positional tracking that makes rendering 3D spatial content possible. This requisite sensing also opens the door for more advanced AR-driven activities, such as augmented perception, volumetric capture and biometric identification - activities with the potential to expose bystanders to significant privacy risks. Existing Privacy-Enhancing Technologies (PETs) often safeguard against these risks at a low level e.g., instituting camera access controls. However, we argue that such PETs are incompatible with the need for always-on sensing given AR headsets' intended everyday use. Through an online survey (N=102), we examine bystanders' awareness of, and concerns regarding, potentially privacy infringing AR activities; the extent to which bystanders' consent should be sought; and the level of granularity of information necessary to provide awareness of AR activities to bystanders. Our findings suggest that PETs should take into account the AR activity type, and relationship to bystanders, selectively facilitating awareness and consent. In this way, we can ensure bystanders feel their privacy is respected by everyday AR headsets, and avoid unnecessary rejection of these powerful devices by society.

show abstract

“…This detection is when a machine is able to understand and detect the human's needs. The context can refer to a behaviour needed within a certain situation used by multiple studies [48,[58][59][60][61][62][63][64][65]. Hugo, the companion, was able to detect and save the participant's queries and requests [58].…”

mentioning

confidence: 99%

“…Human behaviour can be used in many situations-for example, for car interfaces where the car can detect good and bad behaviour of the driver and act upon it [62,65]. Eyecams are able to detect sleepiness in human eyes and mimic it to notify the user [63]. Some bots can detect speech to indicate hate speech and improve the ethics of chatbots [64].…”

mentioning

confidence: 99%

Empathic and Empathetic Systematic Review to Standardize the Development of Reliable and Sustainable Empathic Systems

Daher

Saad

Mugellini

et al. 2022

Sensors

View full text Add to dashboard Cite

Empathy plays a crucial role in human life, and the evolution of technology is affecting the way humans interact with machines. The area of affective computing is attracting considerable interest within the human–computer interaction community. However, the area of empathic interactions has not been explored in depth. This systematic review explores the latest advances in empathic interactions and behaviour. We provide key insights into the exploration, design, implementation, and evaluation of empathic interactions. Data were collected from the CHI conference between 2011 and 2021 to provide an overview of all studies covering empathic and empathetic interactions. Two authors screened and extracted data from a total of 59 articles relevant to this review. The features extracted cover interaction modalities, context understanding, usage fields, goals, and evaluation. The results reported here can be used as a foundation for the future research and development of empathic systems and interfaces and as a starting point for the gaps found.

show abstract

Eyecam: Revealing Relations between Humans and Sensing Devices through an Anthropomorphic Webcam

Abstract: Figure 1: a) Eyecam is an alternative anthropomorphic design of conventional webcams, b) which draws inspiration from the human eye morphology to c) exaggerate the sensing capacities of webcams like face detection, and d) foster affective relationships.

Cited by 15 publications

References 96 publications

“You offer privacy like you offer tea”: Investigating Mechanisms for Improving Guest Privacy in IoT-Equipped Households

“You offer privacy like you offer tea”: Investigating Mechanisms for Improving Guest Privacy in IoT-Equipped Households

Privacy-Enhancing Technology and Everyday Augmented Reality

Empathic and Empathetic Systematic Review to Standardize the Development of Reliable and Sustainable Empathic Systems

Contact Info

Product

Resources

About