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Expressing emotion to others and recognizing emotion state of the counterpart are not difficult for human. Emotion state of a person may be recognized from the facial expression, voice, and/or gesture. Speech emotion recognition research gained a lot of attention in recent years. One of the important subjects in speech emotion recognition research is the feature selection. The speech features used...
This paper presents a method of automatic lexical stress assessment for L2 English speech. Syllable stress can be labeled at three levels - primary (P), secondary (S) and no (N) stress, but secondary stress may vary among word pronunciations within and across accents and present difficulties for human perception. Hence, evaluation of lexical stress based on all three levels (i.e., the P-S-N criterion...
Foreground extraction and moving object detection are often used in human tracking systems. However those methods are not able to produce accurate results when objects are too close or when occlusions happen since the result is generally a single big blob which contains all the different objects. In this paper we propose a novel and efficient moving object detection enhancement method. Indeed, by...
Emotions play a key role in human-computer interaction. They are generally expressed through several ways (e.g. facial expressions, speech, body postures and gestures, etc). In this paper, we present a multimodal approach for the emotion recognition that integrates information coming from different cues and modalities. It is based on a formal multidimensional model using an algebraic representation...
Blocking artifact reduction or deblocking algorithm is an important component in modern block-based video encoding architecture and often used as post-processing procedures in many encoding/transcoding applications. Most of the existing video deblocking algorithms do not take into account Human Visual System(HVS) models and employ empirically designed filters, resulting in suboptimal perceptual image...
Attention-deficit/hyperactivity disorder (ADHD) is a neuropsychiatric disorder which is quite common in childhood, with an estimated prevalence of 5–8%, and often persists into adolescence and adulthood. It is further characterized as inappropriate developmentally symptoms of inattention, impulsiveness, motor over-activity and restlessness. The aim of this study is to evaluate the feasibility of diagnosing...
Due to the maturing of digital image processing techniques, there are many tools, which can edit an image easily without leaving obvious traces to the human eyes. So the authentication of digital images is an important issue in our life. In this paper, multi-resolution Weber law descriptors (WLD) based method that detects copy-move image forgery is introduced. The proposed multi-resolution WLD extracts...
The usage of non-scripted lecture videos as a part of learning material is becoming an everyday activity in most of higher education institutions due to the growing interest in flexible and blended education. Generally these videos are delivered as part of Learning Objects (LO) through various Learning Management Systems (LMS). Currently creating these video learning objects (VLO) is a cumbersome...
Smart vehicle technologies such as ADAS are growing concern about. Especially, pedestrian and vehicle recognition system based on machine vision is a big issue. In this paper, we propose the hardwired HOG feature extractor circuit for real-time human and vehicle detection, and describe the hardware implementation results. Our HOG feature extractor supports weighted gradient value, 2D histogram interpolation...
This paper puts forward a method to extract information from input image and further analyse using that information. However it is relatively difficult to extract the information as the segmentation technique required, is variable between images; a limit of segmentation performance. The main objective of our paper is to propose an algorithm on how to extract that relative information out of given...
This paper presents a low complexity 3D image depth map generation algorithm for embedded stereo applications. The proposed algorithm generates depth information based on a single view 2D image automatically. Owing to different scene characteristics of image, we propose a mechanism to classify images to “Scenery”, “Normal” and “Close-up” types first and generate the associated depth map according...
We propose a method to judge a walker's intention around pedestrian lights by using fuzzy rules. We detect pedestrian object in a movie of crosswalk area by using the code book method and acquire contour information. To improve the processing speed in this stage, we use parallel processing technique based on CUDA (Compute Unified Device Architecture). Now, we remove shadow which causes shape distortion...
This paper proposes a detection method for electronic parts from electronic board images using HSV color format. In this study, we can pick out the electronic parts images by dividing the fixed section. If the parts have a low level of saturation, we detect only two colors that as black and white. To use this method, the detection rate of other colors is improved. It is possible to detect the region...
This paper presents an effective method for human identification using temporal and wavelet domain features extracted from electrocardiogram (ECG) signal. Instead of directly using the ECG data of a person as the feature, first, it is shown that a few number of reflection coefficients extracted from the autocorrelation function of the data can efficiently perform the recognition task. Next, the discrete...
In order to have a rich representation for human action, we propose to combine two complementary features so that a human posture can be characterized in more details. In particular, the distance signal feature and the width feature are combined in an effective way to enhance each other's discriminating capability. The resulting feature vector is quantized into mid-level features using k-means clustering...
This paper introduces the design of a real time vision-based motion synthesis system. the system requires user to wear the markers in a certain color. Based on that, several novel algorithms were used for feature detection and feature tracking under occlusion by estimating the velocity of missing features based on the prior, smoothness and fitness term. These algorithms ensured the accuracy and low...
Detecting objects in underwater image sequences and video frames automatically, requires the application of selected algorithms in consecutive steps. Most of these algorithms are controlled by a set of parameters, which need to be calibrated for an optimal detection result. Those parameters determine the effectivity and efficiency of an algorithm and their impact is usually well known. There are however...
This paper proposes a system to recognize quasi-periodic human actions from monocular video sequences. First, each input video frame is analyzed and estimated to generate the best 3D human model pose which consists of a set of 3D coordinates of specific human joints. Next, these 3D coordinates for each frame are converted into corresponding 3D geometric relational features (GRFs), which describe the...
The human motion analysis is an attractive topic in biometric research. Common biometrics is usually time-consuming, limited and collaborative. These drawbacks pose major challenges to recognition process. Recent researches indicate people have considerable ability to recognize others by their natural walking. Therefore, gait recognition has obtained great tendency in biometric systems. Gait analysis...
This paper presents a multi-feature approach for detection of key postures by using a MESA SR4000 time-offlight 3D sensor managed by a low-power embedded PC. Acquired data were pre-processed by using a well-established framework including self-calibration, segmentation and tracking functionalities. To accommodate different application scenarios, hierarchical coarse-to-fine features were extracted...
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