Embedded Vehicle Speed Estimation System Using an Asynchronous Temporal Contrast Vision Sensor

Bauer, Dietmar; Belbachir, Ahmed Nabil; Donath, N.; Gritsch, G.; Kohn, Bernhard; Litzenberger, M.; Posch, C.; Schön, Peter; Schraml, Stephan

doi:10.1155/2007/82174

Cited by 32 publications

(25 citation statements)

References 5 publications

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“…sign of change from bright to dark or dark to bright) and the time of event generation and thus is a most concise description of the dynamic contents of a scene. While the pixel reacts to illumination changes within microseconds, the DSP allocates time-stamps to the events with one millisecond time resolution, which is sufficient for vehicle detection and speed computation [4,5].…”

Section: A Sensor Systemmentioning

confidence: 99%

“…The results are transmitted over Ethernet to a data receiver for post-processing or storage. More details about the sensor and the setup of the embedded system can be found in [4,5]. allowing us to evaluate our traffic data systems in long-term field tests.…”

Section: A Sensor Systemmentioning

confidence: 99%

“…A comprehensive treatise on speed estimation algorithms employed in similar systems can be found in [5].…”

Section: Introductionmentioning

confidence: 99%

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Vehicle Counting with an Embedded Traffic Data System using an Optical Transient Sensor

Litzenberger¹,

Kohn²,

Gritsch³

et al. 2007

2007 IEEE Intelligent Transportation Systems Conference

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In this paper a sensor system for traffic data acquisition is presented. The embedded system, comprising a motion-sensitive optical sensor and a low-cost, low-power DSP, is capable of detecting, counting and measuring the velocity of passing vehicles. The detection is based on monitoring of the optical sensor output within configurable regions of interest in the sensor's field-of-view. In particular in this work we focus on the evaluation of the applied vehicle counting algorithm. The verification of the acquired data is based on manually annotated traffic data of 360 minutes length, containing a total of about 7000 vehicles. The counting error is determined for short (3 minutes) and long (60 minutes) time intervals. The calculated error of 99,2% of the short time intervals and 100% of the long time intervals analyzed, remain within commonly recognized margins of 10% and 3% of detection error respectively.

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Section: A Sensor Systemmentioning

confidence: 99%

Section: A Sensor Systemmentioning

confidence: 99%

See 1 more Smart Citation

Vehicle Counting with an Embedded Traffic Data System using an Optical Transient Sensor

Litzenberger¹,

Kohn²,

Gritsch³

et al. 2007

2007 IEEE Intelligent Transportation Systems Conference

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“…These devices are gaining increasing popularity and find their way into various fields of machine vision like industrial automation, surveillance and automotive applications [4][5][6]. The pixels employed in these sensors operate autonomously and respond with low latency and high temporal resolution to changes in intensity by generating short continuous-time, digital pulses, called ''spikes'' (for their shape and correlation to biological spike signals).…”

Section: Introductionmentioning

confidence: 99%

A two-stage capacitive-feedback differencing amplifier for temporal contrast IR sensors

Posch¹,

Matolin²,

Wohlgenannt³

2009

Analog Integr Circ Sig Process

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This article presents a small-area, ultra lowpower, low-mismatch differencing transient amplifier for ROIC pixels of micro-bolometer based temporal contrast IR sensors. The two-stage capacitive-feedback amplifier works in the sub-threshold domain, has a voltage gain of 46 dB, a 3 dB bandwidth of about 10 kHz and consumes 85 nW of static power. The amplifier circuit has been fabricated in a 0.35 lm standard CMOS process and consumes less than 2000 lm 2 of silicon area, enabling a square pixel size of 50 9 50 lm for the IR sensor array.

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“…These devices are gaining increasing popularity and find their way into various fields of machine vision like industrial automation, surveillance and automotive applications [4][5] [6]. The pixels employed in these sensors operate autonomously and respond with low latency and high temporal resolution to changes in intensity by generating asynchronous spike events.…”

Section: Introductionmentioning

confidence: 99%

A Two-Stage Capacitive-Feedback Differencing Amplifier for Temporal Contrast IR Sensors

Posch¹,

Matolin²,

Wohlgenannt³

2007

2007 14th IEEE International Conference on Electronics, Circuits and Systems

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This paper presents a small-area, ultra low-power, low-mismatch differencing amplifier for use in transient pixels of micro-bolometer based temporal contrast IR sensors. The two-stage capacitive-feedback amplifier works in the sub-threshold domain, has a voltage gain of 46dB, a 3dB bandwidth of about 10kHz and consumes 85nW of static power. The amplifier circuit has been fabricated in a 0.35µm standard CMOS process and consumes less than 2000µm 2 of silicon area, enabling a square pixel size of 50µm×50µm.

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Embedded Vehicle Speed Estimation System Using an Asynchronous Temporal Contrast Vision Sensor

Cited by 32 publications

References 5 publications

Vehicle Counting with an Embedded Traffic Data System using an Optical Transient Sensor

Vehicle Counting with an Embedded Traffic Data System using an Optical Transient Sensor

A two-stage capacitive-feedback differencing amplifier for temporal contrast IR sensors

A Two-Stage Capacitive-Feedback Differencing Amplifier for Temporal Contrast IR Sensors

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