We present a targetless motion tracking method for detecting planar movements with subpixel accuracy. This method is based on the computation and tracking of the intersection of two nonparallel straight-line segments in the image of a moving object in a scene. The method is simple and easy to implement because no complex structures have to be detected. It has been tested and validated using a l...

We propose to learn pixel-level segmentations of objects from weakly labeled (tagged) internet videos. Specifically, given a large collection of raw YouTube content, along with potentially noisy tags, our goal is to automatically generate spatiotemporal masks for each object, such as “dog”, without employing any pre-trained object detectors. We formulate this problem as learning weakly supervis...

Empathic accuracy (EA)-the correct assessment of the affective states and thoughts of a social partner-affects social behavior and the outcome of interpersonal interactions. Growing evidence has shown that interpersonal power of a perceiver affects EA when assessing a target. This picture, however, is not obvious; there is evidence supporting both the idea that power can improve EA or impair it...

In this paper, a hierarchical system, in which each level is composed by a neural-based classifier, is proposed to recognize objects in underwater images. The system has been designed to help an autonomous underwater vehicle in sea-bottom survey operations, like pipeline inspections. The input image is divided into square regions (macro-pixels) and a neural tree is used to classify each region ...

The formulation of image segmentation as maximum a posteriori probability (MAP) inference over a Markov Random Field (MRF) is both elegant and effective. Typically, the MRF is configured to favour contiguous regions with the same labelling, and consistency between the label at each pixel and prior intensity distributions for foreground and background regions. Boykov and Jolly show how to solve ...

Common per-pixel estimations for vegetation parameters are hampered by spatial mismatch between the image and ground observations, and limited by neglecting spatial patterns. Geometric correction of images can reach accuracies in the range of 1 pixel, while locations of ground observations are measured with an accuracy of 5-10m by GPS. Our HyMap image has 5m pixels. Consequently, although coord...

Mapping of vegetation in mountain areas based on remote sensing is obstructed by atmospheric and topographic distortions. A variety of atmospheric and topographic correction methods has been proposed to minimize atmospheric and topographic effects and should in principle lead to a better land cover classification. Only a limited number of atmospheric and topographic combinations has been tested...

This paper concentrates on designing an object recognition algorithm utilizing image segmentation. The main innovations of this paper lie in that we convert the image segmentation problem into graph cut problem, and then the graph cut results can be obtained by calculating the probability of intensity for a given pixel which is belonged to the object and the background intensity. After the grap...

This paper is devoted to superlensing using hyperbolic metamaterials: the possibility to image an arbitrary object using hyperbolic metamaterials without imposing any conditions on size of the object and the wave length. To this end, two types of schemes are suggested and their analysis are given. The superlensing devices proposed are independent of the object. It is worth noting that the study...