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This paper presents a real-time face detector, named Single Shot Scale-invariant Face Detector (S3FD), which performs superiorly on various scales of faces with a single deep neural network, especially for small faces. Specifically, we try to solve the common problem that anchorbased detectors deteriorate dramatically as the objects become smaller. We make contributions in the following three aspects:...
This paper presents a novel discriminative method for estimating 3D shape from a single image with 3D Morphable Model (3DMM). Until now, most traditional 3DMM fitting methods depend on the analysis-by-synthesis framework which searches for the best parameters by minimizing the difference between the input image and the model appearance. They are highly sensitive to initialization and have to rely...
After intensive research, heterogenous face recognition is still a challenging problem. The main difficulties are owing to the complex relationship between heterogenous face image spaces. The heterogeneity is always tightly coupled with other variations, which makes the relationship of heterogenous face images highly nonlinear. Many excellent methods have been proposed to model the nonlinear relationship,...
Face detection has drawn much attention in recent decades since the seminal work by Viola and Jones. While many subsequences have improved the work with more powerful learning algorithms, the feature representation used for face detection still can't meet the demand for effectively and efficiently handling faces with large appearance variance in the wild. To solve this bottleneck, we borrow the concept...
Due to illumination changes, partial occlusions, and object scale differences, person re-identification over disjoint camera views becomes a challenging problem. To address this problem, a variety of image representations have been put forward. In this paper, the illumination invariance and distinctiveness of different color models including the proposed color model are firstly evaluated. Since color...
LBP is an effective descriptor for face recognition. LBP encodes the ordinal relationship between the neighborhood samplings and the central one to obtain robust face representation. However, additional information like the difference among neighboring pixels, which may be helpful for face recognition, is ignored. On the other hand, gradient information which enhances the edge response and suppresses...
Attributes are helpful to infer high-level semantic knowledge of pedestrians, thus improving the performance of pedestrian tracking, retrieval, re-identification, etc. However, current pedestrian databases are mainly for the pedestrian detection or tracking application, and semantic attribute annotations related to pedestrians are rarely provided. In this paper, we construct an Attributed Pedestrians...
Spoofing attacks mainly include printing artifacts, electronic screens and ultra-realistic face masks or models. In this paper, we propose a component-based face coding approach for liveness detection. The proposed method consists of four steps: (1) locating the components of face; (2) coding the low-level features respectively for all the components; (3) deriving the high-level face representation...
As a crucial security problem, anti-spoofing in biomet-rics, and particularly for the face modality, has achieved great progress in the recent years. Still, new threats arrive in form of better, more realistic and more sophisticated spoofing attacks. The objective of the 2nd Competition on Counter Measures to 2D Face Spoofing Attacks is to challenge researchers to create counter measures effectively...
We present an effective deformable part model for face detection in the wild. Compared with previous systems on face detection, there are mainly three contributions. The first is an efficient method for calculating histogram of oriented gradients by pre-calculated lookup tables, which only has read and write memory operations and the feature pyramid can be calculated in real-time. The second is a...
With the increasing amount of surveillance data, moving object segmentation in the compressed domain has drawn broad attention from both academy and industry. In this paper, we propose a novel moving object segmentation method towards H.264 compressed surveillance videos. First, the motion vectors (MV) are accumulated and filtered to achieve reliable motion information. Second, considering the spatial...
Local binary pattern (LBP) and its variants are effective descriptors for face recognition. The traditional LBP like features are extracted based on the original pixel or patch values of images. In this paper, we propose to learn the discriminative image filter to improve the discriminant power of the LBP like feature. The basic idea is after the image filtering with the learned filter, the difference...
Heterogeneous Face Recognition (HFR) refers recognition of face images captured in different modalities, e.g. Visual (VIS), near infrared (NIR) and thermal infrared (TIR). Although heterogeneous face images of a given person differ by pixel values, the identity of the face should be classified as the same. This paper focuses on NIR-VIS HFR. Light Source Invariant Features (LSIFs) are derived to extract...
Feature selection is an important issue in pattern recognition. In face recognition, one of the state-of-the-art methods is that some feature selection methods (e.g., AdaBoost) are first utilized to select the most discriminative features and then the subspace learning methods (e.g., LDA) are further applied to learn the discriminant subspace for classification. However, in these methods, the objective...
In this paper, we present a method for detecting individuals in crowd by clustering a group of feature points belonging to the same person. In our approach, a feature point is considered to contain three attributes: the motion trajectory in video sequence, the sparse local appearance around point in current frame, and the structure relationship with body center related with local appearance. We exploit...
This study focuses on the design of an intelligent machine vision and sorting system. The vision system uses an artificial neural network trained to perform recognition. A Bluetooth communication link facilitates communication between the intelligent recognition system and a robot control computer. Image feature vectors are transmitted to the remote control computer for recognition and a robot control...
Moving cast shadow removal is an important yet difficult problem in video analysis and applications. This paper presents a novel algorithm for detection of moving cast shadows, that based on a local texture descriptor called Scale Invariant Local Ternary Pattern (SILTP). An assumption is made that the texture properties of cast shadows bears similar patterns to those of the background beneath them...
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