Characterizing the Reconfiguration Latency of Image Sensor Resolution on Android Devices

Hu, Jinhan; Jianan, Yang; Delhivala, Vraj; LiKamWa, Robert

doi:10.1145/3177102.3177109

Cited by 7 publications

(3 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…That is, every time the clock toggles, one pixel gets read out; this happens for all the pixels during the active period. The idle period is the remainder of the time between the frames, as shown in (2). Energy per frame can be calculated in terms of these parameters, as shown in 3:…”

Section: Modeling Active and Idle Powermentioning

confidence: 99%

“…High power consumption is especially common when high precision is required, due to the memory traffic generated by high resolution frames captured at high frame rates. 2 Fortunately, vision algorithms need not operate on full high-resolution frames all of the time. Object tracking can target operations on bounding boxes that follow detected objects to reduce computational workload.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Resolution-Based Tradeoffs for Energy-Efficient Visual Computing Systems

LiKamWa

Kodukula

et al. 2021

IEEE Pervasive Comput.

Self Cite

View full text Add to dashboard Cite

Section: Modeling Active and Idle Powermentioning

confidence: 99%

mentioning

confidence: 99%

Adaptive Resolution-Based Tradeoffs for Energy-Efficient Visual Computing Systems

LiKamWa

Kodukula

et al. 2021

IEEE Pervasive Comput.

Self Cite

View full text Add to dashboard Cite

“…enhanced by continuous capturing, processing, and rendering of visual data through a mobile device. The development of mobile devices and AR frameworks have enabled applications of AR in many fields, including education, entertainment, medicine, navigation, shopping, etc., and the future of AR market is expected to continue its rapid growth [8,18,24,25,42,54].…”

mentioning

confidence: 99%

LensCap

Iosifescu

LiKamWa

2021

Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services

Self Cite

View full text Add to dashboard Cite

Augmented Reality (AR) enables smartphone users to interact with virtual content spatially overlaid on a continuously captured physical world. Under the current permission enforcement model in popular operating systems, AR apps are given Internet permission at installation time, and request camera permission and external storage write permission at runtime through a user's approval. With these permissions granted, any Internet-enabled AR app could silently collect camera frames and derived visual information for malicious intent without a user's awareness. This raises serious concerns about the disclosure of private user data in their living environments.To give users more control over application usage of their camera frames and the information derived from them, we introduce LensCap, a split-process app design framework, in which the app is split into a camera-handling visual process and a connectivityhandling network process. At runtime, LensCap manages secured communications between split processes, enacting fine-grained data usage monitoring. LensCap also allows both processes to present interactive user interfaces. With LensCap, users can decide what forms of visual data can be transmitted to the network, while still allowing visual data to be used for AR purposes on device. We prototype LensCap as an Android library and demonstrate its usability as a plugin in Unreal Engine. Performance evaluation results on five AR apps confirm that visual privacy can be preserved with an insignificant latency penalty (< 1.3 ms) at 60 FPS. CCS CONCEPTS• Security and privacy → Software security engineering.

show abstract

Digital Foveation: An Energy-Aware Machine Vision Framework

Lubana

Dick

2018

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

View full text Add to dashboard Cite

Characterizing the Reconfiguration Latency of Image Sensor Resolution on Android Devices

Cited by 7 publications

References 8 publications

Adaptive Resolution-Based Tradeoffs for Energy-Efficient Visual Computing Systems

Adaptive Resolution-Based Tradeoffs for Energy-Efficient Visual Computing Systems

LensCap

Digital Foveation: An Energy-Aware Machine Vision Framework

Contact Info

Product

Resources

About