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In this paper we propose a novel method called s-DVO for dense visual odometry using a probabilistic sensor noise model. In contrast to sparse visual odometry, where camera poses are estimated based on matched visual features, we apply dense visual odometry which makes full use of all pixel information from an RGB-D camera. Previously, t-distribution was used to model photometric and geometric errors...
Knowledge and experience of a case manager re- mains a key success factor for Case Management Processes (CMPs). When a number of influential parameters is high, a number of possible scenarios grows significantly. Automated guidance in scenario evaluation and activity planning would be of a great help. In our previous work, we defined the statecharts semantics for visualisation and simulation of CMP...
In this paper we discuss the possibility of generating complex networks by multi-swarm Particle Swarm Optimization algorithm. A methodology is proposed and visualizations of created networks are presented. Also we discuss the future possibility of employing advanced complex network analysis to improve the performance of the multi-swarm PSO.
Serious games and simulations are called to fulfill an important role in education. They have already demonstrated effectiveness not only from the point of view of learning, but also as motivation tools. The current work examines the progress that, from the eMadrid Network, is taking place in this research area, together with the new research lines that are being opened.
This paper argues that computational creativity is the logical next step in the evolution of game design; briefly overviews what is meant by computational creativity and suggests some ways in which it could augment contemporary games; explores some initial ideas for its incorporation into the future of gaming and game design; and argues for increased cross-pollination and collaboration between the...
A novel transmission scheme called SoftCast has recently shown a great potential for wireless transmission of visual signals such as images and videos. In this scheme, the visual input signal is processed by a set of linear transformations to produce a sequence of decorrelated transform coefficients. After that, the produced numbers are scaled by separate scaling factors within a power-distortion...
Iterative closest point (ICP) algorithm is a common localization method used to estimate camera poses by aligning two depth frames. Since the input depth map is easily distorted when the camera is in large motion, it might result in incorrect pose estimation and produce apparent drift for ICP-based applications. To alleviate this problem, instead of using the time-consuming graph-based optimization...
In this paper, we present a novel perceptually-based optimization for the improvement of stereoscopic video coding efficiency. The main idea of this proposed scheme is to adaptively adjust the quantization parameter by taking into account the Human Visual System perceptual characteristics. For this, a saliency map is generated from both views and then segmented into salient and non-salient regions...
This paper presents a method for dataset manipulation based on Mixed Integer Linear Programming (MILP). The proposed optimization can narrow down a dataset to a particular size, while enforcing specific distributions across different dimensions. It essentially leverages the redundancies of an initial dataset in order to generate more compact versions of it, with a specific target distribution across...
In the quest of perceptually optimized video coding, coding textures is representing a challenging case. While a large body of research was put into the perception of static textures, dynamic textures are still not sufficiently explored. In this paper, we focus on short term consistent patches, known as dynamic textures, with a very limited spatial and temporal extent. We estimated the visual distortion...
Recently, graph ranking-based methods have been introduced to visual tracking and achieved promising results due to the local structure preserving property. However, existing graph ranking-based trackers use holistic templates to construct the graphs which makes the trackers sensitive to occlusions. In this paper, we propose a part-based multi-graph ranking algorithm for robust visual tracking. In...
Given an image sequence and odometry from a moving camera, we propose a batch-based approach for robust reconstruction of scene structure and camera motion. A key part of our method is robust loop closure disambiguation. First, a structure-from-motion pipeline is used to get a set of candidate feature correspondences and the respective triangulated 3D landmarks. Thereafter, the compatibility of each...
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...
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...
The disadvantages of BOW (Bag of words model) for image classification include the large amount of data in generating a codebook by clustering, redundant code words that may affect the classification results and so on. The process of BOW for the classification can be improved through the Laplace weights to improved fuzzy C means algorithm, and obtaining codebook with more ability to distinguish between...
Brain computer interface (BCI) is a system for communication between people and computers via brain activity. Steady-state visual evoked potentials (SSVEPs), a brain response observed in EEG, are evoked by flickering stimuli. SSVEP is one of the promising paradigms for BCI. Canonical correlation analysis (CCA) is widely used for EEG signal processing in SSVEP-based BCIs. However, the classification...
For action recognition, traditional multitask learning can share low-level features among actions effectively, but it neglects high-level semantic relationships between latent visual attributes and actions. Some action classes might be related, where latent visual attributes across categories are shared among them. In this paper, we improve multitask learning model using attribute-actions relationship...
In recent years, the vast images with user-provided tags are easily available on the photo-sharing platform, which can greatly promote image retrieval and management. However, these tags often are incomplete and noisy, impeding the tag related image applications. To address this challenge, a Sparsity Constrained Low-Rank Matrix Completion (SCLRMC) model is proposed for simultaneously completing and...
In this paper, we propose an approach based on the use of artificial fish swarm algorithm (AFSA) for solving the problem of multicast routing on application layer. Taking delay, stretch, and degree as three optimization objectives, we design the behaviors of artificial fish individual (AF), i.e. moving randomly, preying, following, and use Pareto ranking to evaluate the fitness of AF. The simulation...
This study addresses neural decoding of a code modulated visual evoked potentials (c-VEPs). c-VEP was recently developed, and applied to brain computer interfaces (BCIs). c-VEP BCI exhibits faster communication speed than existing VEP-based BCIs. In c-VEP BCI, the canonical correlation analysis (CCA) that maximizes the correlation between an averaged signal and single trial signals is often used for...
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