Analog VLSI and neural systems
Analog VLSI and neural systems
Wiring considerations in analog VLSI systems, with application to field-programmable networks
Wiring considerations in analog VLSI systems, with application to field-programmable networks
VLSI analogs of neuronal visual processing: a synthesis of form and function
VLSI analogs of neuronal visual processing: a synthesis of form and function
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Advances in Computational Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Efficient Feature Based Matching Algorithm for Stereo Images
GMAI '06 Proceedings of the conference on Geometric Modeling and Imaging: New Trends
| Hi-index | 0.00 |
In this paper we present different approaches of 3D stereo matching for bio-inspired image sensors. In contrast to conventional digital cameras, this image sensor, called Silicon Retina, delivers asynchronous events instead of synchronous intensity or color images. The events represent either an increase (on-event) or a decrease (off-event) of a pixel's intensity. The sensor can provide events with a time resolution of up to 1ms and it operates in a dynamic range of up to 120dB. In this work we use two silicon retina cameras as a stereo sensor setup for 3D reconstruction of the observed scene, as already known from conventional cameras. The polarity, the timestamp, and a history of the events are used for stereo matching. Due to the different information content and data type of the events, in comparison to conventional pixels, standard stereo matching approaches cannot directly be used. Thus, we developed an area-based, an event-image-based, and a time-based approach and evaluated the results achieving promising results for stereo matching based on events.