Titlebook: Image Analysis and Processing — ICIAP 2015; 18th International C Vittorio Murino,Enrico Puppo Conference proceedings 2015 Springer Nature S

Optimum

Fitting Multiple Models via Density Analysis in Tanimoto Spacekage, weakening the prior assumptions on the data: without requiring the tuning of the inlier threshold we develop a new automatic method which takes advantage of the geometric properties of Tanimoto space to bias the sampling toward promising models and exploits a density based analysis in the conc

Heart-Attack

Bag of Graphs with Geometric Relationships Among Trajectories for Better Human Action Recognitionlationships are provided by applying the Delaunay triangulation method on the trajectories of each video frame. Then, graph encoding method called bag of graphs (BOG) is proposed to handle the geometrical relationships between trajectories. BOG considers local graph descriptors to learn a more discr

大約冬季

Have a SNAK. Encoding Spatial Information with the Spatial Non-alignment Kernel recognition performance can be improved by including spatial information. A state of the art approach is the spatial pyramid representation, which divides the image into spatial bins. In this paper, another general approach that encodes the spatial information in a much better and efficient way is

自負(fù)的人

Convolved Multi-output Gaussian Processes for Semi-Supervised Learninge of multiple and related tasks in real-world problems. Another approach called semi-supervised learning (SSL) is the middle point between the case where all training samples are labeled (supervised learning) and the case where all training samples are unlabeled (unsupervised learning). In many appl

Mingle

ASSET

Unsupervised Feature Selection by Graph Optimizationly used criterion in graph based feature selection methods is to select the features which best preserve the data similarity or a manifold structure derived from the entire feature set. However, these methods separate the processes of learning the feature similarity graph and feature ranking. In pra

燒瓶

Gait Recognition Robust to Speed Transition Using Mutual Subspace Methododel to transform gait features from various speeds into a common walking speed, and the model was trained with gait images with a variety of speeds. However in case that a subject walks with a speed which is not trained in the model, the performance gets worse. In this paper we introduce an idea th

襲擊

Limerick

Global and Local Gaussian Process for Multioutput and Treed Datacal tree with parent nodes on the upper layer and children nodes on the lower layer in order to represent the interaction between the multiple outputs.Then we compute the Multiple Output Gaussian Process (MGP) covariance matrix as a linear combination of a global multiple output covariance matrix (u

縮影