Energy proportional image sensors for continuous mobile vision

Robert LiKamWa, Bodhi Priyantha, Matthai Philipose, Lin Zhong, Paramvir Bahl

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A hurdle to frequently performing mobile computer vision tasks is the high energy cost of image sensing. In particular, modern image sensors are not energy proportional; for low resolution and low frame rate capture, the image sensor consumes almost the same amount of energy as it does at high resolutions and high frame rates. We reveal two system-level energy proportional mechanisms: (i) using an optimal pixel clock frequency; (ii) entering low power standby mode between frames. These techniques can be implemented by the image sensor driver with minimal hardware adjustment. Further improvements can be made by designing sensors with heterogeneous hardware architectures. With energy proportionality, computer vision frameworks can be optimized for power consumption, continuously requesting low resolution frames with low energy while only occasionally using high energy to request high resolution frames. This will in turn enable low power continuous mobile vision applications.

Original languageEnglish (US)
Title of host publicationMobiSys 2013 - Proceedings of the 11th Annual International Conference on Mobile Systems, Applications, and Services
Pages467-468
Number of pages2
DOIs
StatePublished - 2013
Externally publishedYes
Event11th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 2013 - Taipei, Taiwan, Province of China
Duration: Jun 25 2013Jun 28 2013

Other

Other11th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 2013
CountryTaiwan, Province of China
CityTaipei
Period6/25/136/28/13

Fingerprint

Image sensors
Computer vision
Hardware
Electron energy levels
Clocks
Electric power utilization
Pixels
Sensors
Costs

Keywords

  • Computer vision
  • Energy efficiency
  • Image sensor
  • Mobile systems

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

Cite this

LiKamWa, R., Priyantha, B., Philipose, M., Zhong, L., & Bahl, P. (2013). Energy proportional image sensors for continuous mobile vision. In MobiSys 2013 - Proceedings of the 11th Annual International Conference on Mobile Systems, Applications, and Services (pp. 467-468) https://doi.org/10.1145/2462456.2483968

Energy proportional image sensors for continuous mobile vision. / LiKamWa, Robert; Priyantha, Bodhi; Philipose, Matthai; Zhong, Lin; Bahl, Paramvir.

MobiSys 2013 - Proceedings of the 11th Annual International Conference on Mobile Systems, Applications, and Services. 2013. p. 467-468.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

LiKamWa, R, Priyantha, B, Philipose, M, Zhong, L & Bahl, P 2013, Energy proportional image sensors for continuous mobile vision. in MobiSys 2013 - Proceedings of the 11th Annual International Conference on Mobile Systems, Applications, and Services. pp. 467-468, 11th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 2013, Taipei, Taiwan, Province of China, 6/25/13. https://doi.org/10.1145/2462456.2483968
LiKamWa R, Priyantha B, Philipose M, Zhong L, Bahl P. Energy proportional image sensors for continuous mobile vision. In MobiSys 2013 - Proceedings of the 11th Annual International Conference on Mobile Systems, Applications, and Services. 2013. p. 467-468 https://doi.org/10.1145/2462456.2483968
LiKamWa, Robert ; Priyantha, Bodhi ; Philipose, Matthai ; Zhong, Lin ; Bahl, Paramvir. / Energy proportional image sensors for continuous mobile vision. MobiSys 2013 - Proceedings of the 11th Annual International Conference on Mobile Systems, Applications, and Services. 2013. pp. 467-468
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