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Chapter and Conference Paper
Experimental Studies of Visual Models in Automatic Image Annotation
Semantic image annotation can be viewed as a map** procedure from image features to semantic labels, by the steps of image feature extraction and image-semantic map**. The features can be low-level visual ...
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Chapter and Conference Paper
Real-Time Plane Segmentation and Obstacle Detection of 3D Point Clouds for Indoor Scenes
Scene analysis is an important issue in computer vision and extracting structural information is one of the fundamental techniques. Taking advantage of depth camera, we propose a novel fast plane segmentation ...
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Chapter and Conference Paper
Adjacency Matrix Construction Using Sparse Coding for Label Propagation
Graph-based semi-supervised learning algorithms have attracted increasing attentions recently due to their superior performance in dealing with abundant unlabeled data and limited labeled data via the label pr...
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Chapter and Conference Paper
Stereo and Motion Based 3D High Density Object Tracking
In order to understand the behavior of adult Drosophila melanogaster (fruit flies), vision-based 3D trajectory reconstruction methods are adopted. To improve the statistical strength of subsequent analysis, high-...
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Chapter and Conference Paper
Video Saliency Modulation in the HSI Color Space for Drawing Gaze
We propose a method for drawing gaze to a given target in videos, by modulating the value of pixels based on the saliency map. The change of pixel values is described by enhancement maps, which are weighted co...
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Chapter and Conference Paper
A Stroke Width Based Parameter-Free Document Binarization Method
This paper presents a parameter-free document binarization method based on text characteristics. For a given stroke width, the text and background regions in binarized object regions are estimated with morphol...
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Chapter and Conference Paper
Novel DCT Features for Detecting Spatial Embedding Algorithms
Traditionally, discrete cosine transform (DCT) features and Cartesian calibration are mainly utilized in joint picture expert group (JPEG) steganalysis. As well known, the steganalyzer without any modification...
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Chapter and Conference Paper
OCR with Adaptive Dictionary
It has been proven by previous works that OCR is beneficial from reducing dictionary size. In this paper, a framework is proposed for improving OCR performance with the adaptive dictionary, in which text categ...
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Chapter and Conference Paper
A New Radiation Correction Method for Remote Sensing Images Based on Change Detection
As an important remote sensing image pre-processing method, radiation correction is essential to reduce deviation introduced by environment factors, especially for tasks such as image compression, image fusion...
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Chapter and Conference Paper
Depth Estimation for Glossy Surfaces with Light-Field Cameras
Light-field cameras have now become available in both consumer and industrial applications, and recent papers have demonstrated practical algorithms for depth recovery from a passive single-shot capture. Howev...
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Chapter and Conference Paper
Activity Recognition in Still Images with Transductive Non-negative Matrix Factorization
Still image based activity recognition is a challenging problem due to changes in appearance of persons, articulation in poses, cluttered backgrounds, and absence of temporal features. In this paper, we propos...
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Chapter and Conference Paper
Robust Segmentation of Aerial Image Data Recorded for Landscape Ecology Studies
Remote sensing from unmanned aerial vehicles provides an opportunity to bridge the gap between fine scale ground-based measurements and broad scale observations from conventional aircraft and satellites. The a...
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Chapter and Conference Paper
Network Intrusion Detection Based on Neural Networks and D-S Evidence
Network traffic data is an important source of data to establish a network intrusion detection system (NIDS). The explosive growth of the network traffic data brings a huge challenge to network intrusion detec...
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Chapter and Conference Paper
The Thermal Infrared Visual Object Tracking VOT-TIR2016 Challenge Results
The Thermal Infrared Visual Object Tracking challenge 2016, VOT-TIR2016, aims at comparing short-term single-object visual trackers that work on thermal infrared (TIR) sequences and do not apply pre-learned mo...
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Chapter and Conference Paper
The Visual Object Tracking VOT2016 Challenge Results
The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a l...
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Chapter and Conference Paper
Online High-Accurate Calibration of RGB+3D-LiDAR for Autonomous Driving
Vision+X has become the promising tendency for scene understanding in autonomous driving, where X may be the other non-vision sensors. However, it is difficult to utilize all the superiority of different senso...
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Chapter and Conference Paper
Efficient Deep Belief Network Based Hyperspectral Image Classification
Hyperspectral Image (HSI) classification plays a key role remote sensing field. Recently, deep learning has demonstrated its effectiveness in HSI Classification field. This paper presents a spectral-spatial HS...
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Chapter and Conference Paper
Lagrange Detector in Image Processing
Edge detection is a basic operation in the field of image processing and computer vision. However, to the best of our knowledge, there is less mathematical work has been proposed beyond the first- and the seco...
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Chapter and Conference Paper
Real-Time Multi-camera Video Stitching Based on Improved Optimal Stitch Line and Multi-resolution Fusion
In this paper, we propose a multi-camera video stitching method based on an improved optimal stitch line and multi-resolution for real-time application. First, phase correlation is used to estimate overlap**...
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Chapter and Conference Paper
An Online Approach for Gesture Recognition Toward Real-World Applications
Action recognition is an important research area in computer vision. Recently, the application of deep learning greatly promotes the development of action recognition. Many networks have achieved excellent per...