The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
It is becoming increasingly clear that it is humanly impossible to analyze a deluge of data from cameras and other sensors in a variety of applications including surveillance, railroad inspection, driver assistance. The practical systems that we built, although in pursuit of different business objectives, share a common goal, which is to intelligently and efficiently analyze and extract the most important...
Finding correspondences between two 3D shapes is common both in computer vision and computer graphics. In this paper, we propose a general framework that shows how to build correspondences by utilizing the isometric property. We show that the problem of finding such correspondences can be reduced to the problem of spectral assignment, which can be solved by finding the principal eigenvector of the...
In this paper, we address an interesting application of computer vision technique, namely classification of Indian Classical Dance (ICD). With the best of our knowledge, the problem has not been addressed so far in computer vision domain. To deal with this problem, we use a sparse representation based dictionary learning technique. First, we represent each frame of a dance video by a pose descriptor...
We are undertaking the development of a brain computer interface (BCI) [1] for control of an upper limb prosthetic. Our approach exploits electrical neural activity data for motor intent estimation, and eye gaze direction for target selection. These data streams are augmented by computer vision (CV) for 3D scene reconstruction, and are integrated with a hierarchical controller to achieve semi-autonomous...
From our ethnographic studies on various kinds of museums, we discovered that guides routinely propose questions to visitors in order to draw their attention towards both his/her explanation and the exhibit. The guides' question sequences tend to begin with a pre-question which serves to not only monitor visitors' behavior and responses, but to also alert visitors that a primary question would follow...
In this paper, we present our work designing a robot that explains an exhibit to multiple visitors in a museum setting, based on ethnographic analysis of interactions between expert human guides and visitors. During the ethnographic analysis, we discovered that expert human guides employ some identical strategies and practices in their explanations. In particular, one of these is to involve all visitors...
We investigate pedestrian detection in depth images. Unlike pedestrian detection in intensity images, pedestrian detection in depth images can reduce the effect of complex background and illumination variation. We propose a new feature descriptor, Histogram of Depth Difference(HDD), for this task. The proposed HDD feature descriptor can describe the depth variance in a local region as Histogram of...
The video sequence which contains certain human action is considered as a spatio-temporal volume. There exists certain characteristic signature in appropriately selected spatio-temporal slice of the video sequence. By using these discriminative signatures which we call “human action logos”, new approaches are proposed for period detection and action recognition. Algorithm performance is evaluated...
Video analysis aiming at efficient pedestrian detection is an important research area in computer vision and robotics. Although this is a well studied topic, successful detection still remains a challenge in outdoor, low resolution images. We present efficient detection metrics which consider the fact that human movement presents some characteristic patterns. Unlike many methods which perform an intra-blob...
in this paper, we propose a new framework in pedestrian detection by combining the HOG and uniform LBP feature on blocks. Contrast experiment result shows that detector using combined features is more powerful than one single feature. To further improve the detection performance, we make a contrast experiment that the HOG-LBP features are calculated at variable-size blocks to find the most efficient...
The automated detection of cell nuclei, which is an important step in the pipeline of quantitative histopathological analysis, has received considerable attentions in recent years. However, biological variations, uneven staining and illumination, non-rigid deformations and touching or overlapping of the cell nuclei have made the detection procedure a major hurdle. In this paper, we consider the problem...
Machine vision is the application of computer vision and related technologies to industrial automation. Automated visual inspection is one of these applications, which can be used to solve many problems in industry. Industrial applications require customized solutions, subject to several particular constraints. The final step of integration of a vision system to an industrial process is not an easy...
Action is any meaningful movement of the human and it is used to convey information or to interact naturally without any mechanical devices. Human action recognition is motivated by some of the applications such as video retrieval, Human robot interaction, to interact with deaf and dumb people etc. In any Action Recognition System, some pre-processing steps are done for removing the noise caused because...
Recent work shows interest-point-based representation is greatly popular in action recognition, due to their simple implementation and good reliability. The neighborhood information of local descriptors usually improves the recognition accuracy. Taking inspiration from this observation, we propose a novel hierarchical neighborhood descriptor for action recognition. At low level, we propose the compound...
We present a novel feature, named Spatio-Temporal Interest Points Chain (STIPC), for activity representation and recognition. This new feature consists of a set of trackable spatio-temporal interest points, which correspond to a series of discontinuous motion among a long-term motion of an object or its part. By this chain feature, we can not only capture the discriminative motion information which...
Tracking human poses in video can be considered as to infer the information of body joints. Among various obstacles to the task, the situation that a body-part occludes another, called ‘self-occlusion,’ is considered one of the most challenging problems. In order to tackle this problem, it is required for a model to represent the state of self-occlusion and to efficiently compute inference, complex...
In this paper we propose a robust pose invariant human detection framework. Most of the existing human detection frameworks assume a standing posture and needing a separate detectors for supporting other human postures. We propose a single framework with a hierarchical tree structure that can detect various poses. The proposed method is based on Randomized trees. Candidate features are selected as...
Local space-time features and bag-of-feature (BOF) representation are often used for action recognition in previous approaches. For complicated human activities, however, the limitation of these approaches blows up because of the local properties of features and the lack of context. This paper addresses the problem by exploiting the spatio-temporal context information between features. We first define...
The Codification of Argopecten Purpuratus is a process, where the Stem and Coral are classified by their weight in different codes. This process is done manually, therefore is linked to the subjectivity and the fatigue of people involved in the work. The use of computer vision is an alternative to automate this process. The present work proposes a method to classify the Argopecten Purpuratus based...
Image segmentation is a fundamental task in computer vision and a prerequisite for many applications. But what is a good segmentation? One possible answer is given by the segmentation-by-composition framework that defines a good segment as one that can easily be composed by parts of itself. However, this framework is originally based on pixels which causes several problems, among them the need for...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.