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Se presenta una revisión teórica acerca del concepto de estereoscopía basado en un análisis detallado del proceso de evolución y del estado del arte. Asimismo, se explica el funcionamiento de la estereoscopía, sus fenómenos y principios y se describe el proceso de visión estereoscópica, los métodos de observación estereoscópica: visión convergente, visión paralela y sus técnicas, separación espectral, separación temporal y separación espacial; las herramientas o artefactos que permiten esta visión y algunas de las aplicaciones más utilizadas en los diferentes campos de las ciencias, como en la reconstrucción de terrenos y la telemedicina.

In this paper, we present EBBIOT-a novel paradigm for object tracking using stationary neuromorphic vision sensors in low-power sensor nodes for the Internet of Video Things (IoVT). Different from fully event based tracking or fully frame based approaches, we propose a mixed approach where we create event-based binary images (EBBI) that can use memory efficient noise filtering algorithms. We exploit the motion triggering aspect of neuromorphic sensors to generate region proposals based on event density counts with > 1000X less memory and computes compared to frame based approaches. We also propose a simple overlap based tracker (OT) with prediction based handling of occlusion. Our overall approach requires 7X less memory and 3X less computations than conventional noise filtering and event based mean shift (EBMS) tracking. Finally, we show that our approach results in significantly higher precision and recall compared to EBMS approach as well as Kalman Filter tracker when evaluated over 1.1 hours of traffic recordings at two different locations.

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