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This paper addresses the problem of person re-identification and its application to a real world scenario. We introduce a retrieval system that helps a human operator in browsing a video content. This system is designed for determining whether a given person of interest has already appeared over a network of cameras. In contrast to most of state of the art approaches we do not focus on searching the...
Non-rigid structure-from-motion in an on-line setting holds many promises for useful applications, and off-line reconstruction techniques are already very advanced. Literature has only recently started focusing on on-line reconstruction, with only a handful of existing techniques available. Here we propose a novel method of history representation which utilizes the advances in off-line reconstruction...
We present a multi-view structured-light system which uses geometric and photometric information observed at multiple viewpoints. In our method, a highly accurate geometry reconstruction is achieved by exploiting our multi-view constraint on unwrapped phase images instead of using photo-consistency between intensity images. Also to express fine 3D information, we directly use photometric normal to...
Person re-identification is the task of associating people across cameras with non-overlapping view field. Two key aspects of Person re-identification are the feature representation and metric learning. The feature representation employed should be both discriminative and invariant, which is also our considering in this paper. To enhance person re-identification performance, we propose to combine...
Challenging ground truth and standardized metrics are a mandatory requirement for the development and evaluation of computer vision algorithms. Despite the significant amount of publications on video based fire detection research it remains difficult to compare different algorithms due to the lack of common evaluation schemes and evaluation datasets. We address both of these issues by presenting a...
Images captured by digital cameras are generally not perfect as image blurring is usually generated by camera motion through long hand-held exposure. Deblurring filters can be used to improve image quality by removing image blur. Prior to develop a deblurring filter, a simulator for image quality assessment is essential to optimize filter parameters. Although subjective image quality assessment (subjective...
Considering the situation that performing indoor positioning system on mobile platform mostly relying on additional wireless signal and known environmental information, we propose an autonomous combination positioning method aimed at continuously estimating metric position and pose in an unknown scene. The vision-based SLAM algorithm extracts the image characteristics of the environment for producing...
RGB-D cameras have attracted much attention in the fields of robotics and computer vision, especially for object modeling and environment mapping. A key problem in all these applications is the registration of sequences of RGB-D images. In this paper, we present an efficient yet reliable approach to align pairs and sequences of RGB-D images that makes use of local surface information. We extend previous...
Semantic mapping is the incremental process of “mapping” relevant information of the world (i.e., spatial information, temporal events, agents and actions) to a formal description supported by a reasoning engine. Current research focuses on learning the semantic of environments based on their spatial location, geometry and appearance. Many methods to tackle this problem have been proposed, but the...
In this paper we present a novel on-line method to recursively align point clouds. By considering each point together with the local features of the surface (normal and curvature), our method takes advantage of the 3D structure around the points for the determination of the data association between two clouds. The algorithm relies on a least squares formulation of the alignment problem, that minimizes...
In this paper, a rank-based manifold ranking (MR) algorithm is proposed for personal re-identification. In general cases, L1 norm, L2 norm, or cos production metrics are frequently adopted for distance or similarity calculation with a heat kernel function. However, outliers in the distance-based scheme always impact the identification results even though the number of outliers is few. A rank-based...
The task of matching persons across non-overlapping camera views, known as person re-identification, is rather challenging due to strong visual similarity and large appearance changes caused by illumination, pose and occlusion. Most approaches rely on low-level features that are both discriminative and invariant. In this work, we propose a novel method to address this problem by fusing mid-level semantic...
Detection, classification, and tracking of people and vehicles are fundamental processes in intelligent surveillance systems. The use of publicly available data set is the appropriate way to compare the relative merits of existing methods and to develop and assess new robust solutions. In this paper, we focus on the maritime domain and we describe the generation of boat classification data sets, containing...
This work presents an approach to detect moving objects from Unmanned Aerial Vehicles (UAV). A common framework for most of the existing techniques is using image registration to warp consecutive frames as an ego-motion compensation step and applying frame differencing to detect the moving objects. Assuming a planar scene, we propose the exploitation of telemetry information available from Global...
Person re-identification is an important computer vision task with many applications in areas such as surveillance or multimedia. Approaches relying on handcrafted image features struggle with many factors (e.g. lighting, camera angle) which lead to a large variety in visual appearance for the same individual. Features based on semantic attributes of a person's appearance can help with some of these...
Histogram of Oriented Gradients is one of the most extensively used image descriptors in computer vision. It has successfully been applied to various vision tasks such as localization, classification and recognition. As it mainly captures gradient strengths in an image, it is sensitive to local variations in illumination and contrast. In the result, a normalization of this descriptor turns out to...
In the paper the idea of the visual self-localization of mobile robots based on the estimation of image similarity is discussed. It is assumed that a rough position of the mobile robot is known e.g. from the built-in GPS device. Assuming known orientation of the robot, the main advantage of the application of image analysis algorithms is the increase of the self-localization accuracy. The basic idea...
Sharpness is an important image quality attribute for projection displays. However, it has not been well studied for projection displays in the existing literature. In this paper, we conduct an experimental study of perceived sharpness on projection displays in a controlled environment. The basic idea is to simulate the optical blurring process with Gaussian filtering and apply them to selected natural...
The 3D-object modeling has become one hottopic in robot vision field for robots locating, grabbing and dropping operation. In this paper, we propose an efficient method of object modeling based RGB-D camera (Kinect) that can help the robot to carry out operation task. Our method is divided into three stage: firstly, point clouds of scene containing object are captured from the camera and plane-segmentation...
Matching observations captured by pedestrian detectors across the cameras with non-overlapping views, known as person re-identification, is challenging due to the appearance changes caused by pose, viewpoint and illumination variations, occlusions and cluttered background. Different from various hand-crafted features, this paper extract the features through the fine-tuned deep convolutional neural...
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