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Although light field data provides abundant cues for depth estimation, light field depth estimation suffers from occlusion and uncertain edges. In this paper, we propose occlusion robust light field depth estimation using segmentation guided bilateral filtering. First, we calculate refocused images from light field data using digital refocusing. Second, we perform support vector machines (SVM) classification...
The task of object tracking in rectangular videos has been addressed in recent years by many researchers, where each method tries to propose a solution for a special challenge. Handling a variety of challenging situation of object tracking in 360-degree videos is still an unsolved problem and needs to be more considered. In the real world, the challenging situations include moving camera, high-resolution...
This paper presents a study that evaluates the performance of multi-view human activity recognition with videos having degraded quality. For the activity recognition models, a support vector machine-based approach using spatiotemporal features and a deep learning-based approach using convolutional and recurrent layers are built. We investigate the recognition performance of the two models with respect...
Due to variations in pose and illumination condition, the appearance of can be significantly different in different cameras and the performance of person re-identification is degraded. In this paper, a person re-identification based on multi-level and multi-feature fusion for this phenomenon is proposed. Firstly, we divided each sample into three parts and multi-layer sampling. Secondly, we extracted...
Mobile robot localization has been considered to be an important task in the field of robotics research. It is known that it is difficult to estimate the self-position in dynamic environments where the positions of objects used as landmarks change. In this paper, we propose a robust method to estimate self-position from the first person view captured by a camera on a robot using Recurrent Convolutional...
This paper presents a solution to the Projective Structure from Motion (PSfM) problem able to deal efficiently with missing data, outliers and, for the first time, large scale 3D reconstruction scenarios. By embedding the projective depths into the projective parameters of the points and views, we decrease the number of unknowns to estimate and improve computational speed by optimizing standard linear...
Accurate ground area detection is one of the most important tasks in various stereo vision based applications, such as autonomous driving or assistive technologies for visually impaired. Correct assertion of the ground geometry improves obstacle detection algorithms by eliminating false positive locations in image. In this paper we provide an application oriented evaluation on the correlation of the...
Diminished reality (DR) enables us to see through real objects occluding some areas in our field of view. This interactive display has various applications, such as see-through vision to visualize invisible areas, work area visualization in surgery and landscape simulation. In this paper, we propose two underlying problems in see-through vision, in which hidden areas are observed in real time. First,...
To robustly estimate the pose, classical methods assume some geometrical and temporal assumptions (SfM: Structure from Motion, SLAM: Simultaneous Localization and mapping). These approaches take a pair of images as input and establish correspondences based on global strategy (using the whole image information) or sparse strategy (using key-points features). These correspondences allow solving a set...
Mobile phones equipped with a monocular camera and an inertial measurement unit (IMU) are ideal platforms for augmented reality (AR) applications, but the lack of direct metric distance measurement and the existence of aggressive motions pose significant challenges on the localization of the AR device. In this work, we propose a tightly-coupled, optimization-based, monocular visual-inertial state...
A method is proposed for estimation of occluded space and generation of auxiliary points for 3D position estimation of strongly occluded objects. First, occlusion space detection calculates 3D keypoints at the rear side of a target object, thus obtaining a silhouette around the object on the near side, as found from a camera image by an object detector. The method calculates the space containing the...
The accuracy and stability are two fundamental concerns of the visual servoing control system. This paper presents an enhanced image based visual servoing (IBVS) method which can increase the accuracy of visual servoing with guaranteed stability. The proposed controller combines PD control with sliding mode control (SMC) for a 6DOF manipulator. Specifically, the main benefits of this approach lie...
Traversable region estimation is the fundamental enabler in autonomous navigation. In this paper, we propose a traversable region segmentation algorithm using stereo vision. We address this problem mainly in road scenes for the goal of autonomous driving. Using only geometry information, our approach has the advantages of effectiveness and robustness. The proposed approach is based on a cascaded framework...
Current light field compression techniques lack robustness to handle both rate-distortion optimized motion compensation as well as latency during the encoding and decoding process. This paper focuses on a contribution approach that uses advanced frame prediction with affine and translational motion models and optimized view prediction structures. This method allows a significant compression performance...
Calibration of multi-projector-camera systems (MPCS) is a cumbersome and time-consuming process. It is of great importance to have robust, fast and accurate calibration procedures at hand for a wide variety of practical applications. We propose a fully automated self-calibration method for arbitrarily complex MPCS. It enables reliable and accurate intrinsic and extrinsic calibration without any human...
In this paper, a temporally iterative Gaussian Mixture Model (GMM) of Dynamic Texture (DT) for target detection using a moving PTZ camera, is proposed. Camera movement in a PTZ sensor causes motion-based target detection techniques to fail for the periods affected by the scene change. This is because the whole scene is considered a representation of the target motion. When the camera is in motion,...
In action recognition, local motion descriptors contribute to effectively representing video sequences where target actions appear in localized spatio-temporal regions. For robust recognition, those fundamental descriptors are required to be invariant against horizontal (mirror) flipping in video frames which frequently occurs due to changes of camera viewpoints and action directions, deteriorating...
In this paper we present new techniques for constructing compact and robust minimal solvers for absolute pose estimation. We focus on the P4Pfr problem, but the methods we propose are applicable to a more general setting. Previous approaches to P4Pfr suffer from artificial degeneracies which come from their formulation and not the geometry of the original problem. In this paper we show how to avoid...
Estimating the 6-DoF pose of a camera from a single image relative to a pre-computed 3D point-set is an important task for many computer vision applications. Perspective-n-Point (PnP) solvers are routinely used for camera pose estimation, provided that a good quality set of 2D-3D feature correspondences are known beforehand. However, finding optimal correspondences between 2D key-points and a 3D point-set...
A cost-effective micro sun sensor is presented for extracting the sun vector from image sensors based on a phenomenon called the black sun. The black sun, appearing as the result of electron overspill at an oversaturated CMOS image pixel when capturing a bright spot such as the sun, allows extracting the sun centroid accurately and robustly even when the sun image appears irregular and noisy due to...
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