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The objective of our work is to reconstruct the dense structure of a static scene observed by a monocular camera system following a known trajectory. Our main contribution is representated by the proposition of a TV-L1 energy functional that estimates directly the unknown depth field given the camera motion, thus avoiding to estimate as an intermediate step an optical flow field with additional geometric...
Time to contact or time to collision (TTC) is the time available to a robot before reaching an object. In this paper, we propose to estimate this time using a catadioptric camera embedded on the robot. Indeed, whereas a lot of works have shown the utility of this kind of cameras in robotic applications (monitoring, localisation, motion,…), a few works deal with the problem of time to contact estimation...
This paper proposes a novel image inpainting method to remove undesired objects in an image. Conventionally, missing regions are filled in using similar textures in an image as exemplars. However, unnatural textures are often generated due to the paucity of available samples. In this study, we take into account symmetric transformation of texture patterns to increase exemplars. To generate plausible...
We propose a novel method to segment the moving object in video clips. In this work, we introduce a region trajectory generation model based on graph clustering. Point trajectories are widely used to measure the motion similarity because of their unambiguity. However, region trajectories preserve object boundaries, while optical flow based point trajectories always ‘over-smooth’ to the background...
A novel statistical framework for modeling the intrinsic structure of crowded scenes and detecting abnormal activities is presented. The proposed framework essentially turns the complex anomaly detection process into two parts: motion pattern representation and spatio-temporal context modeling. We propose a new 4D spatio-temporal hypervolume representation by integrating the depth constraints to enrich...
We propose a technique for removing the appearance of sensor dust in a focal stack image sequence captured with multiple focus settings. Our method is based on the key observation that sensor dust artifacts shift in image position with respect to focus setting, which allows scene information occluded by dust in one image to be inferred from other images in the focal stack. To deal with complications...
The underlying principle behind most optical flow algorithms is that the brightness of a pixel remains the same as it flows from one frame to the next. The first order Taylor approximation used in formulating this brightness constancy principle may not be accurate when intensity profiles change non-linearly. In this paper, we propose a method of alleviating the effect of this approximation. Instead...
This paper presents a variational framework for obtaining super-resolved video-sequences, based on the observation that reconstruction-based Super-Resolution (SR) algorithms are limited by two factors: registration exactitude and Point Spread Function (PSF) estimation accuracy. To minimize the impact of the first limiting factor, a small-scale linear in-painting algorithm is proposed to provide smooth...
Automatically identifying and analyzing head gestures is useful in many situations like smart meeting rooms and intelligent driver assistance. In this paper, we show that head movements can be broken into its elemental forms (i.e. moving and fixation states) and combinations of these elemental forms give rise to various head gestures. Our approach which we term, Optical flow based Head Movement and...
A novel image fusion algorithm performed on the feature level is proposed incorporating with region segmentation and Cauchy convolution. Firstly, the fuzzy c-means clustering algorithm(FCM) is used to segment the image in the space of feature difference, which is formed by dual-tree discrete wavelet transform(DT-DWT) sub-bands. Secondly, the high frequency coefficients are modeled by the convolution...
The hand tremor is one of the most common motion disorders caused by various neurological diseases. Currently diagnostic procedures for tremor evaluation are subjective, and there are no examinations available that can accurately indicate whether tremors are present in a patient's daily life. Early detection of tremor is extremely important for the cure of the disease that causes the tremor. Thus,...
Multispectral endoscopy images provide potential for early stage cancer detection. This paper considers this relatively novel imaging technique and presents a supervised method for cancer detection using such multispectral data. The data under consideration include different types of cancer. This poses a challenge for the detection as different cancer types may exhibit different spectral signatures...
Identifying the boundary of the optic cup excavation is of critical importance in the assessment of glaucomatous risk. Currently, most approaches are focused on the use of pallor. We present an automatic method to determine the cup excavation boundary based on vessel kinking in non-stereo retinal fundus images. The method tracks vessels using a self-initialized evolving model which adapts during propagation...
This paper deals with automatically segmenting a person from challenging videos using a pose detector. A state of the art pose detector is used to detect the pose of a person from a frame in the video sequence. The pose is used to extract color and optical flow features to train a conditional random field to provide segmentation on multiple frames. Location from the pose is used to refine the results...
Databases play an important role in evaluating the performance of fingerprint identification algorithms. But which can be used to test the interoperability? That is to say, few of databases can test the performance of an algorithm on images acquired by different sensors. In order to solve the problem, we create the FingerPass cross-device matching fingerprint database which consists of almost 80 thousand...
In this paper, we address the problem of detecting occlusion boundaries from video sequences. We build a bi-directed graph whose nodes are line fragments extracted from superpixels's edges. Based on the graph, we compute a global occlusion saliency map by integrating motion, shape and topology cues into the framework of Saliency Network. Furthermore, with the structural information generated from...
Traditionally, it was difficult to use vein patterns in evidence images for forensic identification, because they were nearly invisible in color images. We proposed a computational method based on skin optics to uncover vein patterns from color images. However, its performance is dependent on the accuracy of the skin optical model. In this paper, we propose an algorithm based on image mapping to visualize...
We propose a new example-based video upscaling technique that exploits self-similarity among patches of a video in both space and time. We encode image patches with over-complete dictionaries constructed in a local spatio-temporal neighborhood, and establish temporal correspondence using modern optical flow techniques. The resulting method performs favorably compared to the state-of-the-art in super-resolution...
Video summarization, which has a tremendous usage area that spreads from information retrieval to data compression, plays a crucial role in the multimedia understanding. In recent years, with the explosion of the number of videos and their area of use, video summarization became a must to signify. Therefore, this work introduces a novel approach for the summarization problem which is based on human...
Optic cup is the primary image indicator clinically used for identifying glaucoma. To automatically localize the optic cup in fundus images, an effective and efficient superpixel classification based approach is proposed in this work, which maintains both advantages of existing pixel and window based approaches. This method provides three major contributions. First, it proposes processing of the fundus...
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