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The pollen grains of different plant taxa exhibit various shapes and sizes. This structural diversity has made the identification and classification of pollen grains an important tool in many fields. Despite the myriad of applications, the classification of pollen grains is still a tedious and time-consuming process that must be performed by highly skilled specialists. In this paper, we propose an...
Accuracy and efficiency in geoscientific data interpretation is critically important for the resource industry, as based on these interpretations, significant financial decisions are made for exploration and extraction of resources. This study aims to understand image characteristics that impact interpreters' ability to detect geological targets within magnetic geophysics images. We use the Brain...
Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it...
Intelligent personalized systems often ignore the affective aspectof human behavior and focus more on tactile cues of the useractivity. A complete user modeling, though, should also incorporatecues such as facial expressions, speech prosody and gesture orbody posture expressivity features, in order to dynamically profile the user, fusing all available modalities since these qualitative affective cues...
This paper proposes an investigation on classification of the positive and negative emotions via the use of electroencephalogram (EEG). EEG bandpowers are extracted as the feature of interest. Two simple decision rules to classify positive and negative emotions are proposed, i.e. 1) using both the left and right frontal information and 2) using only one side of the left or right frontal information...
Whenever a research scholar starts working on some innovative ideas he/she searches for the domain specific technical research articles published as research papers in most of the international journals, conferences or workshops. The problems associated with these papers are similarity in contents and repeated relevant information. Reading these all relatedpapers completely one by one to get the latest...
Human activity recognition finds many applications in areas such as surveillance, and sports. Such a system classifies a spatio-temporal feature descriptor of a human figure in a video, based on training examples. However many classifiers face the constraints of the long training time, and the large size of the feature vector. Our method, due to the use of an Support Vector Machine (SVM) classifier,...
Biometrics are the personal physiological and behavioral characteristics which are mostly used for personal recognition. Today, biometric based security systems such as fingerprint, iris and face recognition are used everywhere especially in high security areas. Human retina is another source of biometric system which provides the most reliable and stable means of authentication. In this paper, we...
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...
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