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We propose a new approach for detecting repeated patterns on a grid in a single image. To do so, we detect repetitions in the space of pre-trained deep CNN filter responses at all layer levels. These encode features at several conceptual levels (from low-level patches to high-level semantics) as well as scales (from local to global). As a result, our repeated pattern detector is robust to challenging...
This paper presents a robust approach for road marking detection and recognition from images captured by an embedded camera mounted on a car. Our method is designed to cope with illumination changes, shadows, and harsh meteorological conditions. Furthermore, the algorithm can effectively group complex multi-symbol shapes into an individual road marking. For this purpose, the proposed technique relies...
Moving objects detection or change detection in video sequences, is a fundamental task in video surveillance applications. Although, existing methods perform well on videos filmed by stationary cameras, these methods fail dramatically in videos filmed by non-stationary cameras. In particular, in very low frame rate and sudden illumination change scenarios, like Wide-Area Motion Imagery (WAMI). In...
In this paper, a variation in the Local Binary Pattern (LBP) called Modified Dominant Directional LBP (MDDLBP) is proposed. In this method, the direction of the feature with respect to its central pixel in the LBP is preserved by comparing the neighborhood of the pixel in the four dominant directions such as horizontal, vertical, diagonal and anti diagonal. This method captures complete structure...
An analog circuit for maximum power point tracking of a PV battery charger with minimum number of elements is proposed which works in a full range condition with a fixed switching frequency. In conventional MPPT algorithms which provide PV current or voltage reference value as output, fast climate changes may cause system instability. Here, a new variable is defined to eliminate the problem and improve...
We describe a new method of parametric utility learning for non-cooperative, continuous games using a probabilistic interpretation for combining multiple utility functions—thereby creating a mixture of utilities—under non-spherical noise terms. We present an adaptation of mixture of regression models that takes in to account heteroskedasticity. We show the performance of the proposed method by estimating...
Hand gesture plays an important role in nonverbal communication and natural human-computer interaction. However, the complex hand gesture structure and various environment factors lead to low recognition rate. For instance, hand gesture depends on individuals, and different individuals' hands are with different sizes and postures, in addition, unconstrained environmental illumination also influences...
It is a challenging task to develop a robust appearance model due to various factors such as partial occlusion, fast motion, background clutters and illumination variations. In this paper, we propose a novel target representation for visual tracking. Namely, a target candidate is represented by sparse affine combinations of dictionary templates in a particle filter framework. Affine combinations based...
Person re-identification is one of the hot topics in computer vision. How to design a robust feature representation to identify pedestrians is a key problem for person re-identification. In this paper, a feature representation based on Multi-Statistics Cascade on Pyramid (MSCP) is proposed for person re-identification. The MSCP feature is composed of deep PCA network feature and hand-crafted features...
In this paper, real-time recognition and tracking of multiple similar targets at 6-DOF motion is studied. A real-time multi-target recognition algorithm is proposed and implemented based on Marker to solve the difficult problem of distinguishing multiple similar targets. Because the lighting conditions of markers at 6-DOF motion are widely changeable, existing marker recognition algorithms are sensitive...
Vehicle classification plays an important part in Intelligent Transport System (ITS). However, the existing vehicle classification methods are not very robust to various changes such as lighting, weathers, noises, and the classification accuracy has been requiring to be improved. Sparse Representation-based Classifier (SRC) is not sensitive to the shortage and damage of data, the feature selection...
This paper introduces an effective active contour model for texture segmentation. To improve the robustness against noise and illumination, a novel descriptor named local statistical variation degree (LSVD) is presented to express textural features, which uses corner point deletion and isolated region detection operations to eliminate image patches unrelated with object regions. And then the fused...
It has been shown that significant age difference between a probe and gallery face image can decrease the matching accuracy. If the face images can be normalized in age, there can be a huge impact on the face verification accuracy and thus many novel applications such as matching driver's license, passport and visa images with the real person's images can be effectively implemented. Face progression...
This paper presents a novel stereo matching algorithm that utilizes the disparity variations of each pixel by cost formulation in a cooperative manner to solve several stereo disambiguation problems. A completely novel Stereo Orthogonal Feature-mapping transform (SOFT) has been proposed to compute the local as well as semi-global stereo matching cost that involves the extraction of the color information...
Recent studies validated the feasibility of estimating heart rate from human faces in RGB video. However, test subjects are often recorded under controlled conditions, as illumination variations significantly affect the RGB-based heart rate estimation accuracy. Intel newly-announced low-cost RealSense 3D (RGBD) camera is becoming ubiquitous in laptops and mobile devices starting this year, opening...
This paper proposes a robust object tracking algorithm dealing with the occlusion problem and illumination change. In particular, we judge whether each frame image is occluded by the confidence map, and two object spatial-temporal context models are established, one is updated every frame in the process of tracking, and the other is set up before the frame that the object is occluded. This method...
Finding correspondences between two images of the same scene or object, taken from different viewpoints and in different conditions, is a challenging task. Furthermore, in the analysis of scientific imagery, it must be possible in terms of human perception to appreciate detected local features, thus making the task even more complex. A renowned generic feature detector, Maximally Stable Extremal Regions...
Image matching is a classic technique in computer vision. However, the traditional local invariant features image matching algorithm has two problems, narrow scale range and long time consuming. Aiming at these problems, we proposed a fast image matching algorithm with the aid of improved local invariant features based on Locality-Sensitive Hashing. Firstly, by building simple Gaussian pyramid and...
This paper presents a study on the exploitation of visual information from two points of view radically different. Computer vision is a branch of artificial intelligence that focuses on the extraction of useful information in an image. Image matching is a fundamental aspect of many problems in computer vision. Several algorithms have been developed for this purpose. Based on this research, this paper...
In welding inspection and control, radiography imaging technique is one of the most popular methods used in this area. It has a vital role in the detection and the extraction of flaws which may affect the well functioning of many systems. Radiography image processing becomes a difficult task with conventional methods due to the low contrast between flaws and its background, non uniform illumination...
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