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Face detection plays a significant role in many applications, such as video surveillance, gender classification, and facial recognition. In this paper, we propose a new face detection method based on multi-scale histograms. The proposed method uses a multi-scale histogram to represent a face, thereby improving computational efficiency, and making the process suitable for big-data multimedia databases...
We present an image classification method which consists of salient region (SR) detection, local feature extraction, and pairwise local observations based Naive Bayes classifier (NBPLO). Different from previous image classification algorithms, we propose a scale, translation, and rotation invariant image classification algorithm. Based on the discriminative pairwise local observations, we develop...
Traffic sign recognition is difficult due to the low resolution of image, illumination variation and shape distortion. On the public dataset GTSRB, the state-of-the-art performance have been obtained by convolutional neural networks (CNNs), which learn discriminative features automatically to achieve high accuracy but suffer from high computation costs in both training and classification. In this...
There are two different people counting methods: (1) counting people across a detecting line in certain time duration and (2) estimating the total number of people in some region at certain time instance. This paper presents a new approach to count the number of people crossing a line of interest (LOI). First, the foreground object silhouettes are extracted described as blobs. Second, we generate...
To achieve fast and accurate text detection from videos, we propose an efficient coarse-to-fine scheme comprising three stages: key frame extraction, candidate text line detection and fine text detection. Key frames, which are assumed to carry texts, are extracted based on multi-threshold difference of color histogram (MDCH). From the key frames, candidate text lines are detected by morphological...
Most learning-based video semantic analysis methods require a large training set to achieve good performances. However, annotating a large video is laborintensive. This paper introduces how to construct the training set and reduce user involvement. There are four selection schemes proposed: clustering-based, spatial dispersiveness, temporal dispersiveness, and sample-based which can be used construct...
The detection of texts in video images is an important task towards automatic content-based information indexing and retrieval system. In this paper, we propose a texture-based method for text detection in complex video images. Taking advantage of the desirable characteristic of gray-scale invariance of local binary patterns (LBP), we apply a modified LBP operator to extract feature of texts. A polynomial...
In this paper, shot boundary detection (SBD) algorithm based on macroblock and DC image is presented. We get the macroblock type information and simultaneously extract DC images from MPEG compressed domain. The statistics of macroblock type information is applied to coarse detection, and DC images are applied to scrutiny detection. The results of experiments show that our algorithm is efficient, and...
In this paper, we propose a gait analysis method which extracts the dynamic and static information from human walking for walking path and identity recognition. First, we utilize the periodicity of swing distances to estimate the gait period for each gait sequence. For each gait cycle, we extract the dynamic information by analyzing the statistic histogram of motion vectors and static information...
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