Titlebook: Image and Video Technology; 6th Pacific-Rim Symp Reinhard Klette,Mariano Rivera,Shin’ichi Satoh Conference proceedings 2014 Springer-Verlag

scotoma

Vehicle Detection Based on Multi-feature Clues and Dempster-Shafer Fusion Theory, of . Haar-like (AGHaar) features as a promising method for feature classification and vehicle detection in both daylight and night conditions. Validation tests and experimental results show superior detection results for day, night, rainy, and challenging conditions compared to state-of-the-art solutions.

缩减了

Implementation Strategy of NDVI Algorithm with Nvidia Thrust, in RAW format, using the benefits of economic Supercomputing that were obtained by the video cards or Graphics Processing Units (GPU). Our algorithm outperforms other works developed in NVIDIA CUDA, the images used were provided by NASA and taken by Landsat 71 located on the Mexican coast, Ciudad del Carmen, Campeche.

faculty

屈尊

gerrymander

Conference proceedings 2014s are organized in topical sections on image/video processing and analysis, image/video retrieval and scene understanding, applications of image and video technology, biomedical image processing and analysis, biometrics and image forensics, computational photography and arts, computer and robot vision, pattern recognition and video surveillance.

BLAND

0302-9743 of the 6th Pacific Rim Symposium on Image and Video Technology, PSIVT 2013, held in Guanajuato, México in October/November 2013. The total of 43 revised papers was carefully reviewed and selected from 90 submissions. The papers are organized in topical sections on image/video processing and analysi

裙带关系

渐强

RALES

UHDB11 Database for 3D-2D Face Recognition,ger number of subjects. We propose a set of 3D-2D experimental configurations, with frontal 3D galleries and pose-illumination varying probes and provide baseline performance for identification and verification (available at .).

中国纪念碑

Joint Dictionary and Classifier Learning for Categorization of Images Using a Max-margin Framework,rization using a one-vs-all strategy, ignoring relevant correlations among classes. To tackle the previous issues, we propose a novel approach that jointly learns dictionary words and a proper top-level multiclass classifier. We use a max-margin learning framework to minimize a regularized energy fo