Unsupervised feature learning based on sparse coding and spectral clustering for segmentation of synthetic aperture radar images
Synthetic aperture radar (SAR) image segmentation is fundamental for the interpretation and understanding of these images. In this process, the representation of SAR image features plays an important role. Spectral clustering is an image segmentation ...
Auto‐encoder‐based shared mid‐level visual dictionary learning for scene classification using very high resolution remote sensing images
Effective representation and classification of scenes using very high resolution (VHR) remote sensing images cover a wide range of applications. Although robust low‐level image features have been proven to be effective for scene classification, they are ...
Expanding dictionary for robust face recognition: pixel is not necessary while sparsity is
Since sparse representation (SR) was first introduced into robust face recognition, the argument has lasted for several years about whether sparsity can improve robust face recognition or not. Some work argued that the robust sparse representation (RSR) ...
Unsupervised feature selection based on spectral regression from manifold learning for facial expression recognition
In this study, an unsupervised feature selection method is proposed for facial feature recognition (FER) in the absence of class labels. The contribution is the descriptive feature components selector spectral regression representative coefficient scores ...
Enhanced hierarchical model of object recognition based on a novel patch selection method in salient regions
The biologically inspired hierarchical model for object recognition, Hierarchical Model and X (HMAX), has attracted considerable attention in recent years. HMAX is robust (i.e. shift‐ and scale‐invariant), but its use of random‐patch‐selection makes it ...
Discriminating features learning in hand gesture classification
The advent and popularity of Kinect provides a new choice and opportunity for hand gesture recognition (HGR) research. In this study, the authors propose a discriminating features extraction for HGR, in which features from red, green and blue (RGB) images ...
Shape matching algorithm based on shape contexts
This study proposes a novel shape matching algorithm through exploiting shape contexts. The contributions of the proposed algorithm are twofold: (i) a new framework is presented to deal with the shape matching problem based on shape contexts, but ...
Strategy for aesthetic photography recommendation via collaborative composition model
In this study, the authors propose a collaborative composition model for automatically recommending suitable positions and poses in the scene of photography taken by amateurs. By analysing aesthetic‐aware features, the authors' strategy jointly takes ...
Robust tracking with per‐exemplar support vector machine
The authors extend exemplar representation to the field of tracking and propose a robust tracking algorithm with per‐exemplar support vector machine (SVM) classifiers. First, the authors train the simple yet effective exemplar SVM classifier using the ...
Sensor pattern noise and image similarity for picture‐to‐identity linking
Picture sharing through social networks has become a prominent phenomenon, producing a large amount of data that law enforcers may be entitled to use, under the proper legal framework, as a source of information for investigating a crime. In this work, ...
Smartphone image acquisition forensics using sensor fingerprint
- Ana Lucila Sandoval Orozco,
- Luis Javier García Villalba,
- David Manuel Arenas González,
- Jocelin Rosales Corripio,
- Julio Hernandez‐Castro,
- Stuart James Gibson
The forensic analysis of digital images from mobile devices is particularly important given their quick expansion and everyday use in the society. A further consequence of digital images' widespread use is that they are used today as silent witnesses in ...
Individual‐specific management of reference data in adaptive ensembles for face re‐identification
During video surveillance, face re‐identification allows recognition and targeting of individuals of interest from faces captured across a network of video cameras. In such applications, face recognition is challenging because faces are captured under ...
Noise modelling for denoising and three‐dimensional face recognition algorithms performance evaluation
This study proposes an algorithm is proposed to quantitatively evaluate the performance of three‐dimensional (3D) holistic face recognition algorithms when various denoising methods are used. First, a method is proposed to model the noise on the 3D face ...
Shape recognition using orientational and morphological scale‐spaces of curvatures
In this study, a scale‐invariant representation for closed planar curves (silhouettes) is proposed. The orientations of all points within the Gaussian scale‐space of the curve are extracted. This orientation scale‐space is used to create the silhouette ...
Edge detection based on the Shannon Entropy by piecewise thresholding on remote sensing images
Edge detection is one of the most important concepts used in processing of remote sensing images. The aim of edge detection is to mark the points of an image at which the rate of brightness changes sharply. Sharp changes in image features often represent ...
Shape matching and object recognition using common base triangle area
Shape matching has always been a key issue in the field of computer vision. To obtain high recognition accuracy with low time complexity and to reduce the influence of contour deformation due to noise in shape matching, a novel shape matching method based ...
People detection in surveillance: classification and evaluation
Nowadays, people detection in video surveillance environments is a task that has been generating great interest. There are many approaches trying to solve the problem either in controlled scenarios or in very specific surveillance applications. The main ...
