People with low vision who use screen magnifiers to interact with
computing devices find it very challenging to interact with dynamically
changing digital content such as videos, since they do not
have the luxury of time to manually move, i.e., pan the magnifier
lens to different regions of interest (ROIs) or zoom into these ROIs
before the content changes across frames.
In this paper, we present SViM, a first of its kind screen-magnifier
interface for such users that leverages advances in computer vision,
particularly video saliency models, to identify salient ROIs in videos.
SViM’s interface allows users to zoom in/out of any point of interest,
switch between ROIs via mouse clicks and provides assistive
panning with the added flexibility that lets the user explore other
regions of the video besides the ROIs identified by SViM.
Subjective and objective evaluation of a user study with 13 low
vision screen magnifier users revealed that overall the participants
had a better user experience with SViM over extant screen magnifiers,
indicative of the former’s promise and potential for making
videos accessible to low vision screen magnifier users.
more »
« less
You Can't See Me: Providing Privacy in Vision Pipelines via Wi-Fi Localization
Today, video cameras are ubiquitously deployed. These cameras collect, stream, store, and analyze video footage for a variety of use cases, ranging from surveillance, retail analytics, architectural engineering, and more. At the same time, many citizens are becoming weary of the amount of personal data captured, along with the algorithms and datasets used to process video pipelines. This work investigates how users can opt-out of such pipelines by explicitly providing consent to be recorded. An ideal system should obfuscate or otherwise cleanse non-consenting user data, ideally before a user even enters the video processing pipeline itself. We present a system, called Consent-Box, that enables obfuscation of users without using complex or personally-identifying vision techniques. Instead, a user's location on a video frame is estimated via Wi-Fi localization of a user's mobile device. This estimation allows us to remove individuals from frames before those frames enter complex vision pipelines.
more »
« less
- Award ID(s):
- 1908910
- PAR ID:
- 10466885
- Publisher / Repository:
- IEEE
- Date Published:
- ISSN:
- 1944-0375
- ISBN:
- 979-8-3503-4693-0
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Location:
- London, United Kingdom
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)In this paper, we introduce a practical system for interactive video object mask annotation, which can support multiple back-end methods. To demonstrate the generalization of our system, we introduce a novel approach for video object annotation. Our proposed system takes scribbles at a chosen key-frame from the end-users via a user-friendly interface and produces masks of corresponding objects at the key-frame via the Control-Point-based Scribbles-to-Mask (CPSM) module. The object masks at the key-frame are then propagated to other frames and refined through the Multi-Referenced Guided Segmentation (MRGS) module. Last but not least, the user can correct wrong segmentation at some frames, and the corrected mask is continuously propagated to other frames in the video via the MRGS to produce the object masks at all video frames.more » « less
-
null (Ed.)The privacy of users and information are becoming increasingly important with the growth and pervasive use of mobile devices such as wearables, mobile phones, drones, and Internet of Things (IoT) devices. Today many of these mobile devices are equipped with cameras which enable users to take pictures and record videos anytime they need to do so. In many such cases, bystanders’ privacy is not a concern, and as a result, audio and video of bystanders are often captured without their consent. We present results from a user study in which 21 participants were asked to use a wearable system called FacePET developed to enhance bystanders’ facial privacy by providing a way for bystanders to protect their own privacy rather than relying on external systems for protection. While past works in the literature focused on privacy perceptions of bystanders when photographed in public/shared spaces, there has not been research with a focus on user perceptions of bystander-based wearable devices to enhance privacy. Thus, in this work, we focus on user perceptions of the FacePET device and/or similar wearables to enhance bystanders’ facial privacy. In our study, we found that 16 participants would use FacePET or similar devices to enhance their facial privacy, and 17 participants agreed that if smart glasses had features to conceal users’ identities, it would allow them to become more popular.more » « less
-
The EU ePrivacy Directive requires consent before using cookies or other tracking technologies, while the EU General Data Protection Regulation (“GDPR”) sets high-level and principle-based requirements for such consent to be valid. However, the translation of such requirements into concrete design interfaces for consent banners is far from straightforward. This situation has given rise to the use of manipulative tactics in user experience (“UX”), commonly known as dark patterns, which influence users’ decision-making and may violate the GDPR requirements for valid consent. To address this problem, EU regulators aim to interpret GDPR requirements and to limit the design space of consent banners within their guidelines. Academic researchers from various disciplines address the same problem by performing user studies to evaluate the impact of design and dark patterns on users’ decision making. Regrettably, the guidelines and user studies rarely impact each other. In this Essay, we collected and analyzed seventeen official guidelines issued by EU regulators and the EU Data Protection Board (“EDPB”), as well as eleven consent-focused empirical user studies which we thoroughly studied from a User Interface (“UI”) design perspective. We identified numerous gaps between consent banner designs recommended by regulators and those evaluated in user studies. By doing so, we contribute to both the regulatory discourse and future user studies. We pinpoint EU regulatory inconsistencies and provide actionable recommendations for regulators. For academic scholars, we synthesize insights on design elements discussed by regulators requiring further user study evaluations. Finally, we recommend that EDPB and EU regulators, alongside usability, Human-Computer Interaction (“HCI”), and design researchers, engage in transdisciplinary dialogue in order to close the gap between EU guidelines and user studies.more » « less
-
Social media streams analysis can reveal the characteristics of people who engage with or write about different topics. Recent works show that it is possible to reveal sensitive attributes (e.g., location, gender, ethnicity, political views, etc.) of individuals by analyzing their social media streams. Although, the prediction of a user's sensitive attributes can be used to enhance the user experience in social media, revealing some attributes like the location could represent a threat on individuals. Users can obfuscate their location by posting about random topics linked to different locations. However, posting about random and sometimes contradictory topics that are not aligned with a user's online persona and posts could negatively affect the followers interested in her profile. This paper represents our vision about the future of user privacy on social media. Users can locally deploy a cyborg, an artificial intelligent system that helps people to defend their privacy on social media. We propose LocBorg, a location privacy preserving cyborg that protects users by obfuscating their location while maintaining their online persona. LocBorg analyzes the social media streams and recommends topics to write about that are similar to a user's topics of interest and aligned with the user's online persona but linked to other locations.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/LANMAN58293.2023.10189418
