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This paper studies an image descriptor that mimics the retina's photo receiving cell pattern. Various pattern differencing combinations and second order differencing techniques were explored. This new method shows higher precision and recall performance than the classical BRIEF and steered BRIEF descriptors.
Attention of subjects in EEG-based emotion recognition experiments determines the quality of EEG data. Traditionally, self-assessment with questionnaires is used to evaluate the attention degree of subjects in experiments. However, this kind of self-assessment approach is subjective and inaccurate. Low quality EEG data from subjects without attention might influence the experiment evaluation and degrade...
The investors in financial market have shown great concerns in the events that may cause fluctuations in the capital market. Traditional event detection and type recognition methods were majorly based on text processing techniques while few research considers the financial time-series features. As we know, there are large amount of financial time-series data available such as stock transaction data...
For the problem of action detection, most existing methods require that relevant portions of the action of interest in training videos have been manually annotated with bounding boxes. Some recent works tried to avoid tedious manual annotation , and proposed to automatically identify the relevant portions in training videos. However, these methods only concerned the identification in either spatial...
This paper discusses the use of Bag-of-Features and a local part model approach for bare hand dynamic hand gesture recognition from video. We used dense sampling to extract local 3D multiscale whole-part features. We adopted three dimensional histograms of a gradient orientation (3D HOG) descriptor to represent features. K-means++ method has applied to cluster the visual words. Dynamic hand gesture...
In this paper, we present a part model for human action recognition from video. We use 3D HOG descriptor and bag-of-feature to represent video. To overcome the unordered events of bag-of-feature approach, we propose a novel multiscale local part model to preserve temporal context. Our method builds upon several recent ideas including dense sampling, local spatial-temporal (ST) features, 3D HOG descriptor,...
This paper presents a two-level place names identification method based on N-shortest path and conditional random fields (CRFs) aiming at solving the low recall rate problem in Chinese place names identification. First, the rough segmentation method based on N-shortest path is used to improve the recall rate of Chinese place names identification at low level; Second, the result of rough segmentation...
This paper presents an accurate and flexible method for robust recognition and tracking of multiple objects in video sequence. We calculate color moments and wavelet moments for each detected object. Based on the extracted moment features, the SVM achieves optimal object recognition performance. The object recognition rate is above 98.53%. Since the tracking accuracy of feature matching method could...
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