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Stereo images have been captured primarily for 3D reconstruction in the past. However, the depth information acquired from stereo can also be used along with saliency to highlight certain objects in a scene. This approach can be used to make still images more interesting to look at, and highlight objects of interest in the scene. We introduce this novel direction in this paper, and discuss the theoretical...
Six of the ten leading causes of death in the United States, including cancer, diabetes, and heart disease, can be directly linked to diet. Dietary intake, the process of determining what someone eats during the course of a day, provides valuable insights for mounting intervention programs for prevention of many of the above chronic diseases. Measuring accurate dietary intake is considered to be an...
Traditional quality estimators evaluate an image's resemblance to a reference image. However, quality estimators are not well suited to the similar but somewhat different task of utility estimation, where an image is judged instead by how useful it would be in comparison to a reference in the context of accomplishing some task. Multi-Scale Difference of Gaussian Utility (MS-DGU), a reduced-reference...
Determining the make and model of an image's source camera is an important forensic problem. While significant research has been conducted towards developing new camera model identification algorithms, little research has focused on controlling the computational cost of these algorithms. This becomes an important issue if forensic algorithms are to be used in “big data” scenarios. In this paper, we...
Edges in infrared image usually cause serious false alarms in single frame infrared small target detection. So a novel edge-preserving background estimation method is proposed for small target detection to attenuate this problem. First we will introduce the patch similarity feature of infrared image. Then, patch similarity of infrared image is utilized to formulate edge-preserving infrared background...
This method introduces an efficient manner of learning action categories without the need of feature estimation. The approach starts from low-level values, in a similar style to the successful CNN methods. However, rather than extracting general image features, we learn to predict specific video representations from raw video data. The benefit of such an approach is that at the same computational...
Human detection in RGB-D images is an important yet very challenging task in computer vision. In this paper, we propose a novel human detection approach in RGB-D images, which integrates ROI (region-of-interest) generation, depth-size relationship estimation and a human detector. Our approach has the following advantages: 1) ROI generation and depth-size relationship estimation take full advantage...
Professional TV studio footage often poses specific challenges to camera calibration due to lack of features and complex camera operation. As available algorithms often fail, we propose a novel approach based on robust tracking of ellipse and line features of a predefined logo. We further devise a predictive and iterative estimation algorithm, which incorporates confidence measures and filtering....
Robust scale and rotation estimation is an important and challenging problem in visual object tracking. There have been proposed many sophisticated trackers to track the location of a target accurately, but most of them do not take much attention to the scale and rotation estimation. Inspired by the success of the correlation filters in visual tracking, we proposed a novel scale-and-rotation correlation...
This paper investigates precise pupil center localization in low-resolution images. Being an essential preprocessing step in many applications such as gaze estimation, face alignment as well as human-computer interaction, robust, precise, and efficient methods are necessary. We present a method for accurate eye center localization operating with images from simple off-the-shelf hardware such as webcams...
In this paper, we propose a new divide-and-conquer based method, called fusion of multiple binary age-grouping-estimation systems, for human facial age estimation. Under a specific constraint, such as a given facial feature or classification/regression method, what is the better framework for age estimation? First we employ multiple binary-grouping systems for age group classification. Each face image...
Estimation of salient regions in an input video is an active area of research due to its wide applications. In this paper, we propose a novel algorithm to estimate the eye gaze movement in a video using motion, color and structural cues with minimum outliers. The algorithm is generalized to capture salient information for the videos taken under different camera motions. The entire algorithm is parallelizable...
Approximation of the geometric features is an essential step in point cloud segmentation and surface reconstruction. Often, the planar surfaces are estimated using principal component analysis (PCA), which is sensitive to noise and smooths the sharp features. Hence, the segmentation results into unreliable reconstructed surfaces. This article presents a point cloud segmentation method for building...
An analytical characterization of the accuracy of disparity-based autofocus requires an effective error model of disparity estimation. In this paper, we investigate the approximation of photon shot noise of images by a Gaussian model for disparity error analysis that takes defocus blur and image noise into account. We show that, counterintuitively, defocus blur alone does not affect the disparity...
Curvature and torsion of discrete curves are important quantities in numerous applications in 3D image processing. Classical algorithms based on high order derivatives lead to high errors when computing torsion of 3D curves with discrete data of low resolution. To face this challenge we present a discrete parameter free approach to calculate the torsion values without fitting continuous curves on...
Motion estimation across low-resolütion frames and the reconstruction of high-resolütion images are two coupled sübproblems of multi-frame super-resolütion. This paper introduces a new joint optimization approach for motion estimation and image reconstrüction to address this interdependence. Our method is formulated via non-linear least squares optimization and combines two principles of robust süper-resolütion...
Camera calibration denotes the task of estimating the projective mapping between 3D world and the camera image plane. Most of the modern cameras have multiple image and video acquisition modes, which differ in image resolution, field of view or aspect ratio. Each mode should be treated as an independent device, and therefore independently calibrated. This straightforward solution implies the acquisition...
Despite significant progress in pedestrian detection has been made in recent years, detecting pedestrians in crowded scenes remains a challenging problem. In this paper, we propose to use visual contexts based on scale and occlusion cues from detections at proximity to better detect pedestrians for surveillance applications. Specifically, we first apply detectors based on full body and parts to generate...
A novel method, Stochastically Acquired Photoplethysmo-gram for Heart rate Inference in Realistic Environments (SAPPHIRE), is proposed for robust remote heart rate measurement through broadband video. A set of stochastically sampled points from the cheek region is tracked and used to construct corresponding time series observations via skin erythema transforms. From these observations, a photo-plethysmogram...
Appearance model is widely used for image description and demonstrates an impressive performance in object detection. However, most appearance models can not be applied to more freedom object in still image, especially when dealt with variant objects whose shapes are modified by warping, rotation, etc. In this article, a simple but effective method to build a regional rotation-invariant feature descriptor...
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