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Person re-identification (re-id) aims to match a specific person across non-overlapping views of different cameras, which is currently one of the hot topics in computer vision. Compared with image-based person re-id, video-based techniques could achieve better performance by fully utilizing the space-time information. This paper presents a novel video-based person re-id method named Deep Feature Guided...
Person re-identification is one of the hot topics in computer vision. How to design a robust feature representation to identify pedestrians is a key problem for person re-identification. In this paper, a feature representation based on Multi-Statistics Cascade on Pyramid (MSCP) is proposed for person re-identification. The MSCP feature is composed of deep PCA network feature and hand-crafted features...
Due to the wide variety of copy videos, the existing video copy detection methods using single feature face great challenges, especially for video content matching, which are difficult to deal with various copy video transformations. To overcome this problem, a video copy detection method based on sparse representation of MPEG-2 spatial and temporal features is proposed in this paper. Firstly, the...
In this paper, vocabulary tree based large-scale image retrieval scheme is proposed that can achieve higher accuracy and speed. The novelty of this paper can be summarized as follows. First, because traditional Scale Invariant Feature Transform (SIFT) descriptors are excessively concentrated in some areas of images, the extraction process of SIFT features is optimized to reduce the number. Then, combined...
Face diagnosis of Traditional Chinese Medicine (TCM) is carried out by observing the facial complexion to obtain the disease diagnostic results. Color space based on human visual system will be more conducive to facial complexion recognition, which is more suitable to measure and distinguish facial complexion. Uniform color space based facial complexion recognition for TCM is proposed in this paper,...
For the network environment with the limited transmission capacity, a multi-nodes image retrieval method based on visual words is proposed. Firstly, the visual words of query image are built by using the K-means clustering method after the color features and SIFT features of query image are extracted. Then the visual-words histogram of the query image is carried by the mobile Agent. The image similarity...
This paper presents an adaptive edge enhancement method based on histogram matching for ultrasound images. Because of the speckle noises of ultrasound images, traditional edge enhancement methods do not work well for ultrasound images. The proposed method is to seek the regions whose edges needs to be enhanced and ruling out the error edges caused either by speckle noises or the reverberation artifacts...
In this paper, we propose a new unsupervised text detection approach which is based on Histogram of Oriented Gradient and Graph Spectrum. By investigating the properties of text edges, the proposed approach first extracts text edges from an image and localize candidate character blocks using Histogram of Oriented Gradients, then Graph Spectrum is utilized to capture global relationship among candidate...
This paper presents a method for extracting texture and color hybrid features and constructing an adaptive weight operator, which can be used for content-based image retrieval (CBIR). This method extracts texture feature effectively based on Brushlet transform, quantifies in the HSV space, and extracts color feature by color histogram. K-mean clustering is introduced to count overall characteristics...
As a newly emergent biometric technology, finger-vein recognition has attracted more attentions in personal identification. Generally, finger-vein images have low contrast and uneven illumination due to finger-vein imaging manner and finger-shape variation. So, finger-vein enhancement is indispensable for reliable finger-vein network extraction. This paper proposes a new method based on combination...
A novel shape descriptor based on the histogram matrix of pixel-level structural features is presented. First, length ratios and angles between the centroid and contour points of a shape are calculated as two structural attributes. Then, the attributes are combined to construct a new histogram matrix in the feature spacestatistically. The proposed shape descriptor can measure circularity, smoothness,...
Double image compression might occur if the image has been tampered with or embedded into secret data. It is essential to detect double compression for image forensics and blind steganalysis. This paper analyzes the statistical difference in the sub-band DWT (discrete wavelet transform) coefficient histograms between single and double JPEG 2000 compression; devises a scheme to discriminate between...
Nowadays, face detection and recognition have gained importance in security and information access. In this paper, an efficient method of face detection based on principal components analysis (PCA) and support vector machine (SVM) is proposed. It firsly filter the face potential area using statistical feature which is generated by analyzing local histogram distribution. And then, SVM classifier is...
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