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Bipolar Disorder Recognition with Histogram Features of Arousal and Body Gestures
AVEC@MM, 2018This paper targets the Bipolar Disorder Challenge (BDC) task of Audio Visual Emotion Challenge (AVEC) 2018. Firstly, two novel features are proposed: 1) a histogram based arousal feature, in which the continuous arousal values are estimated from the ...
Le Yang +5 more
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2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016
A histogram is an effective form for extracting various types of features and has been attracting keen attention in pattern recognition fields. In visual recognition, however, the histogram features suffer from smoothing due to the processes of quantizing continuous input patterns into discrete codes and pooling them.
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A histogram is an effective form for extracting various types of features and has been attracting keen attention in pattern recognition fields. In visual recognition, however, the histogram features suffer from smoothing due to the processes of quantizing continuous input patterns into discrete codes and pooling them.
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Data Transformation of the Histogram Feature in Object Detection
2010 20th International Conference on Pattern Recognition, 2010Detecting objects in images is very important for several application domains in computer vision. This paper presents an experimental study on data transformation of the feature vector in object detection. We use the modified Pyramid of Histograms of Orientation Gradients descriptor and the SVM classifier to form an object detection model.
Rongguo Zhang +2 more
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Dimensionality reduction for histogram features: A distance-adaptive approach
Neurocomputing, 2016Histogram representations of visual features, such as high dimensional Bag-of-Features (BOF) and Spatial Pyramid Matching (SPM) representation, have been widely studied and adopted in image classification and retrieval due to their simplicity and performance.
Miaomiao Cui, Jiangtao Cui, Hui Li
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The Facial Stress Recognition Based on Multi-histogram Features and Convolutional Neural Network
IEEE International Conference on Systems, Man and Cybernetics, 2018The health disorders due to stress and depression should not be considered trivial because it has a negative impact on health. Prolonged stress not only triggers mental fatigue but also affects physical health.
Barlian Henryranu Prasetio +2 more
semanticscholar +1 more source
Histogram Based Bacteria Colony Features Analysis [PDF]
Key Engineering Materials, 2014 Features analysis is an important task which can significantly affect the performance of automatic bacteria colony picking. This paper presents a novel approach for adaptive colony segmentation by classifying the detected peaks of intensity histograms of images.
Min Rui Fei, Kun Zhang
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Reliable histogram features for detecting LSB matching
2010 IEEE International Conference on Image Processing, 2010This paper proposes a novel steganalyzer for detecting one of the most popular steganography, LSB matching (also known as “±1 embedding”). The histogram of difference image (the differences of adjacent pixels), which is usually a generalized Gaussian distribution centered at 0, is exploited for deriving statistical features.
Kaiwei Cai +4 more
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Similar Region Recommendation Based on Histogram Features
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020When studying landslide hazards and designing road routes, by referring to the research results of regions with similar terrain, the research work can be carried out quickly. The theme of this paper is to recommend several regions with similar terrain for a research region, and the research contents are summarized as follows: first of all, histogram ...
Liu Qiankun +4 more
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Histogram based normalization in the acoustic feature space
IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01., 2005We describe a technique called histogram normalization that aims at normalizing feature space distributions at different stages in the signal analysis front-end, namely the log-compressed filterbank vectors, cepstrum coefficients, and LDA (local density approximation) transformed acoustic vectors.
Michael Pitz, Hermann Ney, Sirko Molau
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Object detection using spatial histogram features
Image and Vision Computing, 2006In this paper, we propose an object detection approach using spatial histogram features. As spatial histograms consist of marginal distributions of an image over local patches, they can preserve texture and shape information of an object simultaneously.
Xilin Chen +3 more
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