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Tracking for planar objects is an important issue to vision-based robotic applications. In direct visual tracking (DVT) methods, the similarity between two images is often measured through the sum of squared differences (SSD) especially with the efficient second-order minimization (ESM) due to its simplicity and efficiency. However, SSD-based ESM is not robust to illumination changes since it is usually...
We propose a novel scoring concept for visual place recognition based on nearest neighbor descriptor voting and demonstrate how the algorithm naturally emerges from the problem formulation. Based on the observation that the number of votes for matching places can be evaluated using a binomial distribution model, loop closures can be detected with high precision. By casting the problem into a probabilistic...
Our work builds upon Visual Teach & Repeat 2 (VT&R2): a vision-in-the-loop autonomous navigation system that enables the rapid construction of route networks, safely built through operator-controlled driving. Added routes can be followed autonomously using visual localization. To enable long-term operation that is robust to appearance change, its Multi-Experience Localization (MEL) leverages...
We propose a vision-based method that localizes a ground vehicle using publicly available satellite imagery as the only prior knowledge of the environment. Our approach takes as input a sequence of ground-level images acquired by the vehicle as it navigates, and outputs an estimate of the vehicle's pose relative to a georeferenced satellite image. We overcome the significant viewpoint and appearance...
Object representation is a major component in object tracking, however, most conventional patch-based methods just simply decompose the object into patches with grid or stochastic rectangles. This kind of decomposition ignores the intrinsic structure of object, leading to low discriminative power and weak representation effectiveness when similar objects appear or under background clutters. In this...
State and input delays are ubiquitous in networked visual servo control systems due to image acquisition, transmission, and processing latencies. In addition, the delays can be time-varying due to network uncertainties and the complexity of the images to be processed. This paper revisits the popular 2.5D visual servo control problem but considers the presence of state and input delays. Specifically,...
Point-based stereo visual odometry systems typically estimate the camera motion by minimizing a cost function of the projection residuals between consecutive frames. Under some mild assumptions, such minimization is equivalent to maximizing the probability of the measured residuals given a certain pose change, for which a suitable model of the error distribution (sensor model) becomes of capital importance...
The change of appearance of the target object is one of important issue in visual tracking. It is because some factors such as camera motion, illumination change, motion change, occlusion, and size change are influenced to the object target during tracking. Recently, discriminative correlation filters (DCF) gave good results to handle these problems. Unfortunately, the DCF only works in the single-resolution...
Development of fast watermarking schemes for all multimedia objects is crucial to the present day research in information security. Besides speed of execution minimizing the trade-off between visual quality and robustness is another important requirement of this research domain. In view of this, a newly developed single layer feedforward network (SLFN) commonly known as Bidirectional Extreme Learning...
In this paper, we address the problem of visual tracking by proposing a novel feature learning technique. Recently, correlation filter based methods have dominated the visual tracking community due to various reasons such as efficient dense matching in frequency domain and simple update strategy. Nevertheless, the studies of correlation filters utilize handcrafted or pre-trained deep features of classification...
Twitter, a well-liked online social networking site, facilitates millions of users on a daily basis to dispatch and orate quick 140-character notes named tweets. Nowadays, Twitter is cogitated as the fastest and popular intermediate of communication and is used to follow latest events. Tweets pertaining to a specific event can be effortlessly found using keyword matching, but there are numerous tweets...
Sub-concussive asymptomatic head impacts during contact sports may develop potential neurological changes and may have accumulative effect through repetitive occurrences in contact sports like American football. The effects of sub-concussive head impacts on the functional connectivity of the brain are still unclear with no conclusive results yet presented. Although various studies have been performed...
The detection of cells and nuclei is a crucial step for the automatic analysis of digital pathology slides and as such for the quantification of the phenotypic information contained in tissue sections. This task is however challenging because of high variability in size, shape and textural appearance of the objects to be detected and of the high variability of tissue appearance. In this work, we propose...
In recent years, several encryption schemes have been proposed to protect data from unauthorized access. It is not suitable to use traditional encryption algorithms for image encryption which were proposed for textual data. The encryption schemes used for images are computationally expensive and power hungry, hence not suitable for mobile phone devices. In this paper, an image encryption scheme is...
This paper presents an improved reversible data hiding algorithm using digital images based on the histogram shifting technique. Proposed method can accurately recover the original image and extract the hidden data accurately. The highest two peak values of the host image's histogram are selected for data hiding. This embedding process is repeated again and again, to attain larger embedding capacity...
Watermarking is an important technical way to realize copyright protection of intellectual property. The traditional video watermarking can cause distortion to host video in a certain extent, and has a weak robustness against strong geometric attacks. Firstly, a Nonnegative Matrix Factorization with Sparseness Constraints on Parts (NMFSCP) method is proposed in this paper. Secondly, the NMFSCP is...
As legged robots maneuver over increasingly complex and rough terrains, designing motion planners with the capability of predicting future footsteps becomes imperative. In turn, these planners provide a valuable tool for understanding the fundamental principles underlying human locomotion [2, 3]. In this study, we use our previously proposed phase-space planning framework [1] to analyze human walking...
Traditional kernelized correlation filter tracking methods use the target position in the current frame to estimate the moving target initial position in the next frame. For fast moving target, these methods lose the target easily. To cope with this problem, a novel scale-adaptive regression position prediction tracking approach is proposed. This algorithm employs regression prediction method to predict...
This paper describes a video fingerprinting system that is highly robust to audio and video transformations. The proposed system adapts a robust audio fingerprint extraction approach to video fingerprinting. The audio fingerprinting system converts the spectrogram into binary images, and then encodes the positions of salient regions selected from each binary image. Visual features are extracted in...
In this paper, we propose to extract robust video descriptor by training deep neural network to automatically capture the intrinsic visual characteristics of digital video. More specifically, we first train a conditional generative model to capture the spatio-temporal correlations among visual contents and represent them as an intermediate descriptor. A nonlinear encoder, with the functions of dimension...
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