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COMPLEX SCENE ANALYSIS IN URBAN AREAS BASED ON AN ENSEMBLE CLUSTERING METHOD APPLIED ON LIDAR DATA
LIDAR Feature Object Extraction Training Fusion Urban Building
2016/3/1
3D object extraction is one of the main interests and has lots of applications in photogrammetry and computer vision. In recent
years, airborne laser-scanning has been accepted as an effective 3D da...
CLUSTERING OF LIDAR DATA USING PARTICLE SWARM OPTIMIZATION ALGORITHM IN URBAN AREA
Clustering LIDAR Particle swarm optimization Urban Area Object Extraction
2016/2/29
One of the fundamental steps in the transformation of the LIDAR data into the meaningful objects in urban area involves their
segmentation into consistent units through a clustering process. Neverth...
Image segmentation based on fuzzy clustering with neighborhood information
image segmentation clustering fuzzy c-means
2011/5/6
In this paper, an improved fuzzy c-means (IFCM) clustering algorithm for image segmentation is presented. The originality of this algorithm is based on the fact that the conventional FCM-based algorit...
Clustering-Based Cascade SVM Assemble fro Adaptive Relevance Feedback Learning
Clustering-Based SVM Adaptive Relevance Feedback Learning
2010/12/17
This paper presents a subspace SVM ensemble algorithm for adaptive relevance feedback (RF) learning. Our method deals with the case that user’s relevance feedback examples are usually insufficient and...
Hierarchical Background Subtraction using Local Pixel Clustering
Hierarchical Background Local Pixel Clustering
2010/12/17
We propose a robust hierarchical background subtraction technique which takes the spatial relations of neighboring pixels in a local region into account to detect objects in difficult conditions. Our ...
Hierarchical Background Subtraction using Local Pixel Clustering
Hierarchical Background Subtraction Local Pixel Clustering
2013/7/17
We propose a robust hierarchical background subtraction technique which takes the spatial relations of neighboring pixels in a local region into account to detect objects in difficult conditions. Our ...
CLUSTERING-BASED SUBSPACE SVM ENSEMBLE FOR RELEVANCE FEEDBACK LEARNING
image retrieval relevance feedback data clustering classifier sampling SVM classifier ensemble
2013/7/17
This paper presents a subspace SVM ensemble algorithm for adaptive relevance feedback (RF) learning. Our method deals with the case that user’s relevance feedback examples are usually insufficient and...
A Two-Phase Spectral Bigraph Co-clustering Approach for the 'Who Rated What' Task
Two-Phase Spectral Bigraph Co-clustering Approach the 'Who Rated What' Task
2010/12/17
This paper describes our approach for the “Who Rated What” task in KDD Cup 2007 competition. Given the Netflix data set that consists of more than 100 million ratings between 1998 and 2005, this task ...
AbstractIn recent years, the explosively growing amount of data in numerous clustering tasks has attracted considerable interest in boosting the existing clustering algorithms to large datasets. In th...
AbstractIn Mobile Ad Hoc Networks (MANET), network partitioning can cause sudden and severe disruptions to ongoing data accesses, and consequently data availability is decreased. A new distributed clu...
An Energy-Efficient Protocol with Static Clustering for Wireless Sensor Networks
Clustering methods energy efficiency routing protocol
2010/2/2
A wireless sensor network with a large number of tiny
sensor nodes can be used as an effective tool for gathering data in
various situations. One of the major issues in wireless sensor
networks is ...
Extracting Story Units in Sports Video Based on Unsupervised Video Scene Clustering
Sports Video Unsupervised Video Scene Clustering
2010/12/16
Many sports videos such as archery, diving and tennis have repetitive structure patterns. They are reliable clues to generate highlights, summarization and automatic annotation.
In this paper, we pre...
UBM Based Speaker Segmentati on and Clustering for 2-Speaker Detection
Speaker segmentation Speaker clustering Multi-speaker Speaker Detection
2013/6/28
In this paper, a speaker segmentation method based on log-likelihood ratio score (LLRS) over universal background model (UBM) and a speaker clustering method based on difference of log-likelihood scor...
Unsupervised Sports Video Scene Clustering and Its Applications to Story Units Detection
Unsupervised Sports Video Scene Clustering Units Detection
2010/12/15
In this paper, we present a new and efficient clustering approach for scene analysis in sports video. This method is generic and does not require any prior domain knowledge. It performs in an unsuperv...
The aim is to facilitate the application of user defined constraints to the genetic clustering algorithm. This is achieved by presenting a general penalty function. The penalty function is defined as ...