Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
We advocate the inference of qualitative information about 3D human pose, called posebits, from images. Posebits represent boolean geometric relationships between body parts (e.g., left-leg in front of right-leg or hands close to each other). The advantages of posebits as a mid-level representation are 1) for many tasks of interest, such qualitative pose information may be sufficient (e.g., semantic...
This paper reports construction of a new device to capture 3D point cloud on human body. The device consists of a horizontal LIDAR, a vertical LIDAR and pan rotational mechanism. The device contain three main features. 1) The device can capture point cloud in large area using combination of the vertical LIDAR and the rotational mechanism. 2) The device can measure dense point cloud using mirror reflection...
Foreground extraction and moving object detection are often used in human tracking systems. However those methods are not able to produce accurate results when objects are too close or when occlusions happen since the result is generally a single big blob which contains all the different objects. In this paper we propose a novel and efficient moving object detection enhancement method. Indeed, by...
A range of automated video analytics systems (VAS) is increasingly being used to improve efficiency and effectiveness within CCTV control rooms. Their role is to manage the large volumes of surveillance data that are constantly generated and to sift the data in real time to detect incidents or activities of specific interest. The CCTV Operator Performance Benchmarking project investigated, through...
In this paper, we consider the problem of tracking human motion with a 22-DOF kinematic model from depth images. In contrast to existing approaches, our system naturally scales to multiple sensors. The motivation behind our approach, termed Multiple Depth Camera Approach (MDCA), is that by using several cameras, we can significantly improve the tracking quality and reduce ambiguities as for example...
We address the problem of robot participation as a team member in group activities. In this human-robot interactive setting, the goal is to enable a robot to detect objects around it using on-board video cameras, and determine which activity they are performing. It then determines how it should move to participate in the activity based on its intended role, derived from domain knowledge, and human...
Service robots that work together with humans in domestic and constantly changing environments should have a general understanding about their human partners and the tasks that are to be performed. This would enable them to verify their beliefs about the common tasks and the goals of their human partners and detect unexpected events and failures. In this paper we present a way of acquiring general,...
We propose a model-based approach for human body pose recognition from a single-view depth camera. The proposed algorithm applies an articulated cylinder model to detect human pose and track them based on a particle filter without numerous training data or heuristic detectors. To reduce high degrees of freedom, we adopt a hierarchical method that detects torso and limbs successively. Moreover, we...
In the field of video surveillance, multiple object tracking is a challenging problem in the real application. In this paper, we propose a multiple object tracking method by spatiotemporal tracklet association. Firstly, reliable tracklets, the fragments of the entire trajectory of individual object movement, are generated by frame-wise association between object localization results in the neighbor...
When human locomotion is used to interact with virtual or augmented environments, the system's immersion could be improved by providing reliable information about the user's walking intention. Such a prediction can be derived from tracking data to determine the future walking direction. This paper analyses how tracking data relates to navigation decisions from an egocentric view in order to achieve...
In this paper, we present a novel generative method for human motion tracking. The principle contribution is the development of clonal selection algorithm for pose analysis in latent space of human motion. Firstly, we use ISOMAP to learn the low-dimensional latent space of pose state and a manifold reconstruction method is proposed to establish the smooth mappings between the latent and original space...
As a certain case in the domain of human actions, hand gestures can be expressed by the motion of user's hand to provide nature interaction in many applications. In this paper we proposed a real-time hand gesture recognition system based on robust hand tracking from depth image sequences. Using hidden markov models (HMM) with varying states, gesture models are trained online along with user's feedback,...
Natural interaction between application user of a Virtual Environment (VE) and autonomous characters is a key challenge in enhancing the realism in virtual environments. Traditional interaction methods with autonomous characters such as virtual humans using keyboard and mouse do not provide an intuitive user experience. This paper presents an approach that enables user to communicate and control virtual...
A picture is worth a thousand words. To take advantage of powerful human vision, we generate visualizations for people to view and to understand the underlying data. However, these a thousand words do not necessarily tell the truth about the data. A good visualization can make the data understanding process effective, while a bad visualization may hinder the process, even convey misleading information...
Model based methods to marker-free motion capture have a very high computational overhead. In this paper we describe a method that improves on existing global optimization techniques to tracking articulated objects. Our method improves on the state-of-the-art Annealed Particle Filter (APF) by reusing samples across annealing layers and by using an adaptive parametric density for diffusion. We compare...
Visually tracking a large number of objects remains a trade-off between accuracy and amount of data. For applications where high accuracy in both position and orientation of points in space is required, optical tracking systems with passive marker systems are suitable. However, the placement of the marker dots remains problematic, as distin-guishability between the marker alignments considerably reduces...
We propose a method that relies on markerless visual observations to track the full articulation of two hands that interact with each-other in a complex, unconstrained manner. We formulate this as an optimization problem whose 54-dimensional parameter space represents all possible configurations of two hands, each represented as a kinematic structure with 26 Degrees of Freedom (DoFs). To solve this...
Human activity recognition has potential to impact a wide range of applications from surveillance to human computer interfaces to content based video retrieval. Recently, the rapid development of inexpensive depth sensors (e.g. Microsoft Kinect) provides adequate accuracy for real-time full-body human tracking for activity recognition applications. In this paper, we create a complex human activity...
Humans are still responsible for operating complex equipment because they are able to respond during emergency situations. By removing the pilot from an aircraft, Unmanned Air Vehicles (UAVs) are vulnerable to unpredictable activity within their environment. The landing process is the most stressful phase of flight for pilots and as a consequence, a significant number of UAV are being destroyed or...
In this paper, a novel sparse feature representation method for object tracking is proposed. The method is on the observation that a tracked object can be dynamically and compactly represented by a few features (sparse representation) from a large feature set (the improved histogram of oriented gradient and color, HOGC). Based on the HOGC features, the sparse representation can be learned online from...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.