Titlebook: Computer Vision - ECCV ‘96; Fourth European Conf Bernard Buxton,Roberto Cipolla Conference proceedings 1996 Springer-Verlag Berlin Heidelbe

嚴峻

書目名稱Computer Vision - ECCV ‘96影響因子(影響力)




書目名稱Computer Vision - ECCV ‘96影響因子(影響力)學科排名




書目名稱Computer Vision - ECCV ‘96網(wǎng)絡公開度




書目名稱Computer Vision - ECCV ‘96網(wǎng)絡公開度學科排名




書目名稱Computer Vision - ECCV ‘96被引頻次




書目名稱Computer Vision - ECCV ‘96被引頻次學科排名




書目名稱Computer Vision - ECCV ‘96年度引用




書目名稱Computer Vision - ECCV ‘96年度引用學科排名




書目名稱Computer Vision - ECCV ‘96讀者反饋




書目名稱Computer Vision - ECCV ‘96讀者反饋學科排名

微不足道

Texture feature coding method for classification of liver sonography,d a . co-occurrence matrix which will produce texture feature descriptors. By coupling with a supervised maximum likelihood (ML) classifier, these descriptors form a classification system to discriminate the three above-mentioned liver classes. The TFCM-supervised ML system is trained by 30 liver sa

存在主義

https://doi.org/10.1007/978-3-642-79739-2nsional subspace even under severe variation in lighting and facial expressions. The Eigenface technique, another method based on linearly projecting the image space to a low dimensional subspace, has similar computational requirements. Yet, extensive experimental results demonstrate that the propos

pancreas

mydriatic

Self-calibration from image triplets,ly via the trifocal tensor between image triplets; third, a robust and automatic implementation of the method..Results are included of affine and metric calibration and structure recovery using images of real scenes.

Aviary

Class based reconstruction techniques using singular apparent contours,bility even under large noise. This work has added to the accumulating body of work that has arisen in the computer vision community, concerning the differential geometric aspects of special surface classes.

Aviary

watertight,

KIN

Oriented projective geometry for computer vision, system of cameras, while extending its adequation to model realistic situations..We discuss the mathematical and practical issues raised by this new framework for a number of computer vision algorithms. We present different experiments where this new tool clearly helps.

藐視

Fast computation of the fundamental matrix for an active stereo vision system,form for an active stereo system. We demonstrate that typical variations in camera intrinsic parameters do not much affect the epipolar geometry in the image. This motivates us to calibrate the camera intrinsic parameters approximately and then to use the calibration results to compute the epipolar geometry directly in real time.