What Catches Your Eyes as You Move Around? On the Discovery of Interesting Regions in the Street

Chi, Heng‐Yu; Cheng, Winton; You, Chuang-Wen; Chen, Ming-Syan

doi:10.1007/978-3-319-27671-7_64

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…People cannot only deliver but access multimedia data anywhere on the Internet in a short time. These multimedia data, especially the images and videos, are frequently used in computer vision application, for instance, feature detection, object recognition [2], visual surveillance [3], photo clustering, and virtual navigation in photos [4,5]. However, some security issues exist because of open unsafe networks.…”

Section: Introductionmentioning

confidence: 99%

Quantization-based image authentication scheme using QR error correction

2017

J Image Video Proc.

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Image authentication, which is provided with capabilities of tamper detection and data recovery, is an efficient way to protect the contents of digital images. Vector quantization (VQ) is a data compression method. A VQcompressed code is not only a significant image authentication feature but also applicable in restoring possibly damaged pixels. However, if an image is tampered with, the necessary recovery information disappears. To solve this problem, this paper proposes a quantization-based image authentication scheme using two-dimensional (2D) barcodes to protect important features. Compared with older linear barcodes, 2D barcodes are a machine-readable representation of binary data that possess capabilities of location and tolerance. This paper presents a method for incorporating VQ-compressed code into 2D barcodes and embedding those barcodes into the image itself. Experimental results showed that VQ codes can be completely reserved during data recovery even though quick response codes sustain certain perceptible distortions. Moreover, the proposed scheme provided higher quality authenticated and recovered images compared with previous methods.

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Section: Introductionmentioning

confidence: 99%

Quantization-based image authentication scheme using QR error correction

2017

J Image Video Proc.

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Eyes and Apps on the Streets: From Surveillance to Sousveillance Using Smartphones

Ceccato

2019

Criminal Justice Review

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This article explores the concept of surveillance by assessing the nature of data gathered by users of a smartphone-based tool (app) developed in Sweden to assist citizens in reporting incidents in public spaces. This article first illustrates spatial and temporal patterns of records gathered over 9 months in Stockholm County using Geographic Information Systems (GIS) to exemplify the process of sousveillance via app. Then, the experiences of user group members, collected using an app-based survey, are analyzed. Findings show that the incident reporting app is more often used to report an incident and less often to prevent it. Preexistent social networks in neighborhoods are fundamental for widespread adoption of the app, often used as a tool in Neighborhood Watch schemes in highcrime areas. Although the potentialities of using app data are open, these results call for more indepth evaluations of smartphone data for safety interventions.

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What Catches Your Eyes as You Move Around? On the Discovery of Interesting Regions in the Street

Cited by 2 publications

References 12 publications

Quantization-based image authentication scheme using QR error correction

Quantization-based image authentication scheme using QR error correction

Eyes and Apps on the Streets: From Surveillance to Sousveillance Using Smartphones

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