Low Power Motion Detection with Low Spatial and Temporal Resolution for CMOS Image Sensor

Verdant,; Dupret,; Mathias,; Villard,; Lacassagne,

doi:10.1109/camp.2007.4350342

Cited by 3 publications

(4 citation statements)

References 11 publications

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“…Study [29] suggested that power consumption of video sensors depends on the frame size and frame rate, but without conducting actual experiments. This paper considers the popular CMOS sensors and develops a power consumption model based on extensive experiments.…”

Section: Video Capturing Power Consumptionmentioning

confidence: 99%

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Aggregate power consumption modeling of live video streaming systems

Sharrab

Sarhan

2013

Proceedings of the 4th ACM Multimedia Systems Conference

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Power consumption of video streaming systems has become a major concern, especially in battery-powered devices, such as video sensors. Power is usually dissipated in each one of the major phases of the streaming process: capturing, encoding, and transmission. This paper develops models for power consumption in each of these phases and validates them with extensive experiments, focusing primarily on H.264 video encoding. For comparative purposes, we also study MJPEG and MPEG-4 video codecs. In addition, we analyze the impacts of the main H.264 video compression parameters on power consumption and bitrate. These parameters include quantization parameter, number of reference frames, motion estimation (ME) range, and ME algorithm.

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Section: Video Capturing Power Consumptionmentioning

confidence: 99%

“…By substituting Equation (29) in Equation (28), we can model the power consumption as a function of the bitrate:…”

Section: Impact Of the Quantization Parameter (Qp )mentioning

confidence: 99%

Aggregate power consumption modeling of live video streaming systems

Sharrab

Sarhan

2013

Proceedings of the 4th ACM Multimedia Systems Conference

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“…In [6], various low-resolution modes have been considered from a motion detection point of view. This study shows that lower false alarm rates are achieved by reducing image resolution using macropixels, without decreasing detection rates.…”

Section: Introductionmentioning

confidence: 99%

“…In our context of embedded steady camera for video surveillance [6], [7], SystemC modeling of our architecture allowed to ensure system coherence and motion detection algorithm robustness regards to technological parameters such as noise or mismatch, while giving a first order of power consumption.…”

Section: Introductionmentioning

confidence: 99%

SystemC validation of a low power analog CMOS image sensor architecture

Verdant

Villard

Dupret³

et al. 2007

2007 IEEE Northeast Workshop on Circuits and Systems

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In a context of embedded steady camera for video surveillance with high performance requirements and hard power consumption constraints, a low power CMOS image sensor architecture allowing sensor's acuity adaptation to the scene activity is considered. In this paper we present an original approach based on SystemC modeling to validate a complex analog SIMD architecture (i.e. highly parallel and programmable) and the implemented algorithm.

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