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Recently, many works have been published for counting people. However, when being applied to real-world train station videos, they have exposed many limitations due to problems such as low resolution, heavy occlusion, various density levels and perspective distortions. In this paper, following the recent trend of regression-based density estimation, we present a linear regression approach based on...
We propose a novel middle level estimation of traffic scenes: Collision Risk Rating (CRR). Given a video sequence from a dashboard camera as input, the objective is to estimate a rate that describes "how likely a collision could happen". CRR's problem setting is similar to that of video classification, but it is more complicated and requires rich feature representations to capture the different...
Estimating speaker's physical parameters like height, weight and shoulder size can assist in voice forensics by providing additional knowledge about the speaker. In this work, statistics of the components of background GMM are employed as features in estimating the physical parameters. These features improved the performance of height and shoulder size estimation as compared to our earlier attempt...
Cuff-less blood pressure (BP) estimation using pulse transit time (PTT) is a promising method for long-term BP monitoring. However, state-of-art PTT models are unable to trace the change of pressure baseline in subjects, which limits their application in long-term BP tracking. This study investigated the relationship between the change of pressure baseline and pulse waveform in long-term BP monitoring...
The maximum consensus problem lies at the core of several important computer vision applications as it is one of the most popular criteria for robust estimation. Although considerable efforts have been devoted to solving this problem, exact algorithms are still impractical for real-world data. Randomized hypothesize-and-test approaches such as RANSAC and its variants are therefore still the key players...
The number of triangles in a graph is useful to deduce a plethora of important features of the network that the graph is modeling. However, finding the exact value of this number is computationally expensive. Hence, a number of approximation algorithms based on random sampling of edges, or wedges (adjacent edge pairs) have been proposed for estimating this value. We argue that for large sparse graphs...
Within the context of road estimation, the present paper addresses the problem of the fusion of several sources with different reliabilities. Thereby, reliability represents a higher-level uncertainty. This problem arises in automated driving and ADAS due to changing environmental conditions, e.g., road type or visibility of lane markings. Thus, we present an online sensor reliability assessment and...
Recently, Electroencephalogram (EEG) has become increasingly important in the role of psychiatric diagnosis and emotion recognition. However, many irrelevant features make it difficult to identify patterns accurately. Obtaining valid features from electroencephalogram can improve the classification and generalization performance. In this paper, an improved normalized mutual information feature selection...
In 3D object recognition, local feature-based recognition is known to be robust against occlusion and clutter. Local feature estimation requires feature correspondences, including feature extraction and matching. Feature extraction is normally a two-stage process that estimates keypoints and keypoint descriptors, and existing studies show repeatability to be a good indicator of keypoint feature detector...
A novel composite approach through integration of variational optical flow and surface splines is presented to obtain sub-pixel accurate dense disparity map for remotely sensed stereo image pair. It is well known that, surface splines handle geometric distortion very well. The performance of surface splines for dense correspondence can be significantly improved by the reliable control points, but...
This paper proposed a novel method to improve automatic age estimation from human faces. Three types of feature extraction algorithms are used, such as Extended Curvature Gabor Filter (ECG), Completed Local Binary Pattern (CLBP), and Local Directional Pattern (LDP). While the ECG is applied to the entire human face, CLBP and LDP are only applied to blocks with randomized scales, positions and orientations...
This paper presents a novel method for interest level estimation based on matrix completion via rank minimization. The proposed method estimates interest levels of target objects from human behavior features which are extracted during selecting these objects. Specifically, by adopting matrix completion via rank minimization, unknown interest levels can be estimated. Furthermore, the proposed method...
The brain produces weak electrical signals that can be measured from the skull. Electroencephalography (EEG) is a method that provides monitoring electrical activity of the brain with the electrical methods. Brain Computer Interface (BCI) is a system that converts the electrical signals produced by the brain to the signals that can be interpreted by a computer or an electronic system. Brain Computer...
Stereo matching is important in the area of computer vision and photogrammetry. We present a stereo matching algorithm to refine depth map by using stereo image pair. The reference image is segmented by using hill-climbing algorithm and Scale Invariant Feature Transform (SIFT) feature descriptor with Sum of Absolute Difference (SAD) local stereo matching is performed. Next, we extract a set of disparity...
This paper presents a new method for video preference estimation using functional near-infrared spectroscopy signals (fNIRS signals). The proposed method first computes fNIRS features from fNIRS signals recorded while users are watching videos and multiple visual features from these videos. Next, by applying Locality Preserving Canonical Correlation Analysis to fNIRS features and each visual feature,...
Research efforts have been devoted to extraction and visualization of vortices in an unsteady (turbulent) flow. Characterizing the behaviors of the flow, vortices are identifiable as regions using a vortex detector known as the lambda2-criterion. Isosurface visualization renders vortex regions based on a chosen isovalue. However, it is highly challenging to choose one isovalue suitable for visualizing...
In this paper we develop a fault detection and isolation method based on data-driven approach. Data-driven methods are effective for feature extraction and feature analysis using statistical techniques. In the proposal, the Cumulated Sum (CUSUM) efficiency is explored for incipient fault detection. The fault is assumed to be a Gain variation, an Offset evolution, a Phase shifting or one of the multiple...
The monitoring of a cutting tool is needed for the prediction of impending faults and estimating its Remaining Useful Life (RUL). Implementing a robust Prognostic and Health Management (PHM) system for a high speed milling CNC cutter remains a challenge for various industries to reach improved quality, reduced downtime, increased system safety and lower production costs. The purpose of the present...
There is a nonlinear relation between the blood glucose and photoplethysmography(PPG) signal. In order to estimate the blood glucose from the photoplethysmography signal, this paper presents a non-invasive blood glucose estimation using Near-Infrared spectroscopy based on the Support Vector Regression(SVR). The wavelet transform algorithm is used to remove baseline drift and smooth signals. 22 parameters,...
Appearance-based gaze estimation methods have received increasing attention in the field of human-computer interaction (HCI). These methods tried to estimate the accurate gaze point via Convolutional Neural Network (CNN) model, but the estimated accuracy can't reach the requirement of gaze-based HCI when the regression model is used in the output layer of CNN. Given the popularity of button-touch-based...
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