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In this paper, a unified deep convolutional architecture is proposed to address the problems in the person re-identification task. The proposed method adaptively learns the discriminative deep mid-level features of a person and constructs the correspondence features between an image pair in a data-driven manner. The previous Siamese structure deep learning approaches focus only on pair-wise matching...
Manipulation of beacons is a method of Human-Swarm Interaction (HSI) of relative ease to implement, especially for computer simulated environments. This paper focuses on doing an in depth analysis of an implementation of attractor and repulsor fields and determining its advantages and disadvantages through experimental means. The results give an optimistic view of the method: the learning curve is...
Pairwise surface rigid registration aims to find the rigid transformation that best register two surfaces represented by point clouds. This work presents a comparison between seven algorithms, with different strategies to tackle rigid registration tasks. We focus on the frame-to-frame problem by using both point clouds and a RGB-D video stream in the experimental results. The former, is considered...
Person re-identification is a challenge in video-based surveillance where the goal is to identify the same person in different camera views. In recent years, many algorithms have been proposed that approach this problem by designing suitable feature representations for images of persons or by training appropriate distance metrics that learn to distinguish between images of different persons. Aggregating...
This work introduces a novel surface registration method based on foliation. A foliation decomposes the surface into a family of closed loops, such that the decomposition has local tensor product structure. By projecting each loop to a point, the surface is collapsed into a graph. Two homeomorphic surfaces with consistent foliations can be registered by first matching their foliation graphs, then...
This paper presents an adaptive version of the path planning algorithm based on the recently proposed structure called bur of free configuration space. The original planning algorithm — rapidly exploring bur tree (RBT) is based on the multi-directional extension of tree nodes for efficient exploration of free configuration space. A suitable number of directions for extension (extension degree) was...
Modelling of a database performance depending on numerous factors is the first step towards its optimization. The linear regression model with optional parameters was created. Regression equation coefficients are optimized with the Flower Pollination metaheuristic algorithm. The algorithm is executed with numerous possible execution parameter combinations and results are discussed. Potential obstacles...
Networks are typically embedded in non-homogeneous areas and different parts/regions of the network may therefore be at risk from different types of disasters. This non-homogeneity leads to difficulties in protecting the network against (the risk of) disasters. Network operators need to be able to integrate predictions on possible future disaster events in the planning of their network operation....
With the widely using of network-on-chip in VLSI systems, mapping has been one of the most critical and general problem in VLSI design and test. In this paper, a breadth-first greedy algorithm is proposed to reduce internal congestion and solve the application mapping with the structure of the task topology and the shape of the mapping area. The experimental results show our solution achieves the...
We propose an effective optimization algorithm for a general hierarchical segmentation model with geometric interactions between segments. Any given tree can specify a partial order over object labels defining a hierarchy. It is well-established that segment interactions, such as inclusion/exclusion and margin constraints, make the model significantly more discriminant. However, existing optimization...
We present a new distance measure between sequences that can tackle local temporal distortion and periodic sequences with arbitrary starting points. Through viewing the instances of sequences as empirical samples of an unknown distribution, we cast the calculation of the distance between sequences as the optimal transport problem. To preserve the inherent temporal relationships of the instances in...
The Gromov-Hausdorff (GH) distance is traditionally used for measuring distances between metric spaces. It was adapted for non-rigid shape comparison and matching of isometric surfaces, and is defined as the minimal distortion of embedding one surface into the other, while the optimal correspondence can be described as the map that minimizes this distortion. Solving such a minimization is a hard combinatorial...
We present a Riemannian framework for linear and quadratic discriminant classification on the tangent plane of the shape space of curves. The shape space is infinite dimensional and is constructed out of square root velocity functions of curves. We introduce the idea of mean and covariance of shape-valued random variables and samples from a tangent space to the pre-shape space (invariant to translation...
In this paper, we present a new benchmark (Menpo benchmark) for facial landmark localisation and summarise the results of the recent competition, so-called Menpo Challenge, run in conjunction to CVPR 2017. The Menpo benchmark, contrary to the previous benchmarks such as 300-W and 300-VW, contains facial images both in (nearly) frontal, as well as in profile pose (annotated with a different markup...
Object-Based Image Analysis (OBIA) has gained swift popularity in remote sensing area mainly due to the increasing availability of very high resolution imagery. Image segmentation is a major step within OBIA process. Image segmentation quality remarkably influences the subsequent image classification accuracy. It is necessary to implement advanced and robust methods to increase image segmentation...
Developing multimedia embedded applications continues to flourish. In fact, a biometric facial recognition system can be used not only on PCs abut also in embedded systems, it is a potential enhancer to meet security and surveillance needs. The analysis of facial recognition consists offoursteps: face analysis, face expressions’ recognition, missing data completion and full face recognition. This...
We propose an alternative to the common approaches to the topological segmentation in structured or unstructured environments, Contour-Based Segmentation. It is faster and equally accurate, without the need of fine tuning parameters or heuristics. During robotic exploration, we propose an incremental version that reduces the processing time by reusing the previous segmentation. Tests demonstrate the...
Semi-supervised clustering has been widely explored in the last years. In this paper, we present HCAC-ML (Hierarchical Confidence-based Active Clustering with Metric Learning), an innovative approach for this task which employs distance metric learning through cluster-level constraints. HCAC-ML is based on the HCAC algorithm, an state-of-the-art algorithm for hierarchical semi-supervised clustering...
Exhausters and coexhausters were proposed by V.F. Demyanov and is used for studying nonsmooth functions. These objects are families of convex compact sets in terms of which optimality conditions are described. This makes possible to construct effective optimization algorithms for nonsmooth problems. Exhausters and coexhausters are not uniquely defined. The smaller families the easier computations...
Code smells are sub-optimal coding circumstances such as blob classes or spaghetti code - they have received much attention and tooling in recent software engineering research. Higher-up in the abstraction level, architectural smells are problems or sub-optimal architectural patterns or other design-level characteristics. These have received significantly less attention even though they are usually...
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