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.
In order to have a rich representation for human action, we propose to combine two complementary features so that a human posture can be characterized in more details. In particular, the distance signal feature and the width feature are combined in an effective way to enhance each other's discriminating capability. The resulting feature vector is quantized into mid-level features using k-means clustering...
As human action is uncertain and illegible, a human action recognition method basing on fuzzy support vector machine is presented. Fuzzy support vector machine employs the membership function to solve the unclassifiable areas which happens the traditional SVMs' two-class problems extend to the multi-class problems. the method is evaluated on the Weizmann action dataset and received comparative high...
This paper presents a unified action recognition framework combining harris3D descriptor with 3D SIFT detector. We perform action recognition experiments on the KTH dataset using Support Vector Machines. Experiments apply the leave-one-out and compare our proposed approach with state-of-the-art methods. The result shows that our proposed approach is effective. Compared with other approaches our approach...
We consider in-hand manipulation tasks that consists of periodic movements. In order to improve the manipulation learning ability of a robot with a human-like hand, this paper introduces a segmentation method based on the techniques of action gist. Action gist is the key motion information in manipulation with the property of semantics. In the techniques of in-hand manipulation action gist, there...
Pose tracking technique has great potential for many applications such as marker-free human motion capture system, Human Computer Interactions (HCI), and video surveillance. Though many methods are introduced during last decades, self-occlusion - one body part is occluded by another one - is still considered one of the most difficult problems for 3D human pose tracking. In this paper, we propose a...
In human body pose estimation, manifold learning is a useful method for reducing the dimension of 2D images and 3D body configuration data. Most commonly, body pose is estimated from silhouettes derived from images or image sequences. A major problem when applying manifold estimation, however, is its vulnerability to silhouette variation. In this paper, we propose a novel approach to solving viewpoint-induced...
Play is a vital activity in which children observe the world, learn new concepts and experiment with them. Even though the social aspect of play is very important, the computer science community has struggled to address it. Digital playgrounds have been built in which children can play in technologically enhanced installations, but the detailed study of the social component of play within these installations...
Category 4. A machine learning based methodology is proposed to recognize a predefined set of hand gestures using depth images. For such purpose, a RGBD sensor (Microsoft kinect) is employed to track the hand position. Thus, a preprocessing stage is presented to subtract the region of interest from depth images. Moreover, a learning algorithm based on kernel methods is used to discover the relationships...
This paper proposes a novel system for automatically detecting children from a color monocular back-up camera, as part of a back-up warning device in passenger vehicles. We presented the use of an attentional mechansim that focuses compute-intensive bounding-box classifiers on a subset of all possible bounding-box solutions to enable real-time performance of 248ms per frame with negligible reduction...
We present a novel dataset for evaluation of object matching and recognition methods in surveillance scenarios. Dataset consists of more than 23,000 images, depicting 15 persons and nine vehicles. A ground truth data -- the identity of each person or vehicle -- is provided, along with the coordinates of the bounding box in the full camera image. The dataset was acquired from 36 stationary camera views...
Due to the development of World Wide Web technologies, people are living in the place flooding trillions of web pages in every moment. The amount of web size has been increasing dramatically. For this reason, it is getting more difficult to find relevant web documents corresponding to what users want to read. Classifying documents into predefined categories is one of the most important tasks in Natural...
Humans are poorly equipped to perform repetitive tasks without adversely affecting the efficiency with which they are performing the task. Assets within a secure environment are usually protected with various controls that are enforced by users who follow operational controls associated to those assets. The current approach to security monitoring by means of video cameras are performed by a person...
In this paper we propose an approach to recognize human actions using depth images. Here, we capture the motion dynamics of the object from the depth difference image and average depth image. The features from the space-time depth difference images are obtained from hierarchical division of the silhouette bounding box. We also make use of motion history images to represent the temporal information...
Human action classification is an important task in computer vision. The Bag-of-Words model uses spatio-temporal features assigned to visual words of a vocabulary and some classification algorithm to attain this goal. In this work we have studied the effect of reducing the vocabulary size using a video word ranking method. We have applied this method to the KTH dataset to obtain a vocabulary with...
Local spatiotemporal detectors and descriptors have recently become very popular for video analysis in many applications. They do not require any preprocessing steps and are invariant to spatial and temporal scales. Despite their computational simplicity, they have not been evaluated and tested for video analysis of facial data. This paper considers two space-time detectors and four descriptors and...
Computer vision is a field that includes methods for acquiring, processing, analyzing and understanding images. In the embedded world, computer vision applications have to fight with limited processing power and limited resources to achieve optimized algorithms and high performance. This paper presents work on implementing a human tracking system on both Intel based PC platform and embedded systems...
Falls are a major threat to the independence and quality of life of elderly people. As the worldwide population of elderly increases each year, responding to falls is essential. Computer vision systems provide a new promising solution in responding falls through detecting fall events. This paper presents a new technique in detecting falls based on human shape variation. The proposed visual based fall...
This paper demonstrates how 3D skeletal reconstruction can be performed by using a pose-sensitive embedding technique applied to multi-view video recordings. We apply our approach to challenging low-resolution video sequences. Usually skeletal reconstruction can be only achieved with many calibrated high-resolution cameras, and only blob detection can be achieved with such low-resolution imagery....
This paper presents the conceptual and architectural design of a multilayered framework aiming to provide a two handed gesture based visual interactive 3D object oriented environment for software development. We argue that this is a viable, intuitive and attractive approach for software development facilitating natural human computer interaction, thus supporting tasks related to software development...
Temporal alignment of human motion has been a topic of recent interest due to its applications in animation, telerehabilitation and activity recognition among others. This paper presents generalized time warping (GTW), an extension of dynamic time warping (DTW) for temporally aligning multi-modal sequences from multiple subjects performing similar activities. GTW solves three major drawbacks of existing...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.