CINECA IRIS Institutional Research Information System
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishThis paper presents a new hardware-oriented approach for the extraction of disparity maps from stereo images. The proposed method is based on the herein named Adaptive Census Transform that exploits adaptive support weights during the image transformation; the adaptively weighted sum of SADs is then used as the dissimilarity metric. Quality tests show that the proposed method reaches significantly better accuracy than alternative hardware-oriented approaches. To demonstrate the practical hardware feasibility, a specific architecture has been designed and its implementation has been carried out using a single FPGA chip. Such a VLSI implementation allows a frame rate up to 68 fps to be reached for 640 × 480 stereo images, using just 80,000 slices and 32 RAM blocks of a Virtex6 chip.
Adaptive Census transform: A novel hardware-oriented stereovision algorithm / Perri, Stefania; Corsonello, Pasquale; Cocorullo, Giuseppe. - In: COMPUTER VISION AND IMAGE UNDERSTANDING. - ISSN 1077-3142. - 117:1(2013), pp. 29-41.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
| Titolo: | Adaptive Census transform: A novel hardware-oriented stereovision algorithm | |
| Autori: | ||
| Data di pubblicazione: | 2013 | |
| Rivista: | ||
| Citazione: | Adaptive Census transform: A novel hardware-oriented stereovision algorithm / Perri, Stefania; Corsonello, Pasquale; Cocorullo, Giuseppe. - In: COMPUTER VISION AND IMAGE UNDERSTANDING. - ISSN 1077-3142. - 117:1(2013), pp. 29-41. | |
| Handle: | http://hdl.handle.net/20.500.11770/139127 | |
| Appare nelle tipologie: | 1.1 Articolo in rivista |
File in questo prodotto:
http://hdl.handle.net/20.500.11770/139127
Copyright © 2021