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The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Previous approaches to drowsiness detection primarily make pre-assumptions about the relevant behavior, focusing on blink rate, eye closure, and yawning. Here(More)
This paper presents a fast face recognition algorithm that combines the discrete cosine transform based local appearance face recognition technique with the local binary pattern (LBP) representation of the face images. The underlying idea is to benefit from both the robust image representation capability of local binary patterns, and the compact(More)
Performance of current face recognition algorithms reduces significantly when they are applied to low-resolution face images. To handle this problem, super-resolution techniques can be applied either in the pixel domain or in the face subspace. Since face images are high dimensional data which are mostly redundant for the face recognition task, feature(More)
The aging population in developed countries has shifted considerable research attention to diseases related to age. Because age is one of the highest risk factors for neurodegenerative diseases, the need for automated brain image analysis has significantly increased. Magnetic resonance imaging (MRI) is a commonly used modality to image brain. MRI provides(More)
Today, with quality becoming increasingly important, each product requires three-dimensional in-line quality control. On the other hand, the 3D reconstruction of transparent objects is a very difficult problem in computer vision due to transparency and specularity of the surface. This paper proposes a new method, called Scanning From Heating (SFH), to(More)
The objective of this work is to develop an algorithm for the detection of vehicles in parking lot images. By the proposed method, each image region corresponding to a parking cell is segmented for initialization and temporal differencing is used for state tracking. Therefore, reference images taken in vacant state are not needed. The algorithm can easily(More)
This paper presents a new approach for segmentation of multiple brain structures. We introduce a new coupled shape prior for neighboring structures in magnetic resonance images (MRI) for multi object segmentation problem, where the information obtained from images can not provide enough contrast or exact boundary. In segmentation of low contrasted brain(More)
This paper presents a new facial feature localization system which estimates positions of eyes, nose and mouth corners simultaneously. In contrast to conventional systems, we use the multi-stream Gaussian mixture model (GMM) framework in order to represent structural and appearance information of facial features. We construct a GMM for the region of each(More)
The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Here we employ machine learning techniques to detect driver drowsiness. The system obtained 98% performance in predicting driver drowsiness. This is the(More)
Combining implicit polynomials and algebraic invariants for representing and recognizing complicated objects proves to be a powerful technique. However, a basic requirement for using implicit polynomials for affine invariant recognition is to have an affine invariant fitting algorithm. In this paper, we study the problem of affine invariant fitting of an(More)