A fast area-based stereo matching algorithm
By Luigi Di Stefano, M. Marchionni, Stefano Mattoccia. Image and Vision Computing, 2004
344 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Media Technology
View Paper: https://www.semanticscholar.org/paper/ec52725a4ecc1135cd526147e0e7c85fa53dbb27
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- J. Aguilera
- Jie Shan
- Roberto Quevedo
- Lorenzo Bruzzone
- Antonios Gasteratos
- Georgios Sirakoulis
- Li Shen
- Yuanxin Ye
In Media Technology
- Jie Shan
- Yuanxin Ye
- J. Aguilera
- Roberto Quevedo
- Lorenzo Bruzzone
- Antonios Gasteratos
- Georgios Sirakoulis
- Nalpantidis Lazaros
Citations in the corpus
- Robust Registration of Multimodal Remote Sensing Images Based on Structural Similarity (2017, methodology): “To increase the robustness of the image matching, a bidirectional matching technique [41] is applied, which includes two steps (forward matching and backward matching).”
- Review of Stereo Vision Algorithms: From Software to Hardware (2008, methodology): “Another fast area-based stereo matching algorithm, which uses the SAD as error function, is presented in (Di Stefano et al. 2004).”
- Computer Vision and Stereoscopy for Estimating Firmness in the Salmon (Salmon salar) Fillets (2010, methodology): “The settings of the camera used in our experiments are summarized in Table 1. Under the camera, the system has a base that allows the samples to move in a parallel direction (up to 13 cm) in relation to the shift, to take two images of the same scene (left and right images; Fig. 1). The displacement”