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This paper proposes a novel high-order local pattern descriptor, local derivative pattern (LDP), for face recognition. LDP is a general framework to encode directional pattern features based on local derivative variations. The n(th)-order LDP is proposed to encode the (n-1)(th) -order local derivative direction variations, which can capture more detailed(More)
This paper proposes a novel Kernel Similarity Modeling of Texture Pattern Flow (KSM-TPF) for background modeling and motion detection in complex and dynamic environments. The Texture Pattern Flow encodes the binary pattern changes in both spatial and temporal neighborhoods. The integral histogram of Texture Pattern Flow is employed to extract the(More)
This paper introduces a new BeiHang (BH) Keystroke Dynamics Database for testing and evaluation of biometric approaches. Different from the existing keystroke dynamics researches which solely rely on laboratory experiments, the developed database is collected from a real commercialized system and thus is more comprehensive and more faithful to human(More)
Active Shape Model (ASM) is one of the most popular methods for image alignment. To improve its matching accuracy, in this paper, ASM searching method is combined with a simplified Elastic Bunch Graph Matching (EBGM) algorithm. Considering that EBGM is too time-consuming, landmarks are grouped into contour points and inner points, and inner points are(More)
Gabor wavelet related feature extraction and classification is an important topic in image analysis and pattern recognition. Gabor features can be used either holistically or analytically. While holistic approaches involve significant computational complexity, existing analytic approaches require explicit correspondence of predefined feature points for(More)
Feature extraction and classification using Gabor wavelets have proven to be successful in computer vision and pattern recognition. Gabor feature based Elastic Bunch Graph Matching (EBGM), which demonstrated excellent performance in the FERET evaluation test, has been considered as one of the best algorithms for face recognition due to its robustness(More)
Human-centric driver assistance systems with integrated sensing, processing and networking aim to find solutions for traffic accidents and other relevant issues. The key technology for developing such a system is the capability of automatically understanding and characterizing driver behaviors. This paper proposes a novel driving posture recognition(More)
This paper presents a new Multidirectional Binary Pattern (MBP) for face recognition. Different from most Local Binary Pattern (LBP) related approaches which cluster LBP occurrences from whole image or partitioned subimage patches and use single or conca-tenated histogram measurement for recognition, MBP is applied on a sparse set of shape-driven points.(More)