Group Action Recognition Using Space-Time Interest Points

Abstract. Group action recognition is a challenging task in computer vision due to the large complexity induced by multiple motion patterns. This paper aims at analyzing group actions in video clips containing sev-eral activities. We combine the probability summation framework with the space-time (ST) interest points for this task. First, ST interest points are extracted from video clips to form the feature space. Then we use k-means for feature clustering and build a compact representation, which is then used for group action classification. The proposed approach has been applied to classification tasks including four classes: badminton, tennis, basketball, and soccer videos. The experimental results demon-strate the advantages of the proposed approach.

Exploiting Metric Structure for Efficient Private Query Release

We consider the problem of privately answering queries defined on databases which are collections of points belonging to some metric space. We give simple, computationally efficient algorithms for answering distance queries defined over an arbitrary metric. Distance queries are specified by points in the metric space, and ask for the average distance from the query point to the points contained in the database, according to the specified metric. Our algorithms run efficiently in the database size and the dimension of the space, and operate in both the online query release setting, and the offline setting in which they must in polynomial time generate a fixed data structure which can answer all queries of interest. This represents one of the first subclasses of linear queries for which efficient algorithms are known for the private query release problem, circumventing known hardness results for generic linear queries

Optical interface states protected by synthetic Weyl points

Weyl fermions have not been found in nature as elementary particles, but they emerge as nodal points in the band structure of electronic and classical wave crystals. Novel phenomena such as Fermi arcs and chiral anomaly have fueled the interest in these topological points which are frequently perceived as monopoles in momentum space. Here we report the experimental observation of generalized optical Weyl points inside the parameter space of a photonic crystal with a specially designed four-layer unit cell. The reflection at the surface of a truncated photonic crystal exhibits phase vortexes due to the synthetic Weyl points, which in turn guarantees the existence of interface states between photonic crystals and any reflecting substrates. The reflection phase vortexes have been confirmed for the first time in our experiments which serve as an experimental signature of the generalized Weyl points. The existence of these interface states is protected by the topological properties of the Weyl points and the trajectories of these states in the parameter space resembles those of Weyl semimetal "Fermi arcs surface states" in momentum space. Tracing the origin of interface states to the topological character of the parameter space paves the way for a rational design of strongly localized states with enhanced local field.Comment: 36 pages, 9 figures. arXiv admin note: text overlap with arXiv:1610.0434

Online Klassifikation menschlicher Aktionen anhand von Space-Time Interest-Points

Panzner M. Online Klassifikation menschlicher Aktionen anhand von Space-Time Interest-Points. Bielefeld: Universität Bielefeld; 2013.Human motion classification is an important area of computer vision with a variety of applications in surveillance, human-computer interfaces and robotics. Many current systems for human motion classification rely on a batch processing scheme to learn their classification model. This excludes these systems from many possible applications where fast response to new classes of stimuli is necessary. This thesis will present two approaches for incremental online classification of human motion, which will allow the system to adapt to new situations on the fly, without the need to go through the whole batch learning process again. The developed algorithms are tested against a current state of the art offline classification system, which already has shown good results on several human motion databases. It will be shown, that the developed online classification systems can archive competitive results while avoiding several limitations of the offline approaches

Relevance of interest points for eye position prediction on videos

2009, XIV, 456 p., Softcover. ISBN: 978-3-642-04666-7International audienceThis papers tests the relevance of interest points to predict eye movements of subjects when viewing video sequences freely. Moreover the papers compares the eye positions of subjects with interest maps obtained using two classical interest point detectors: one spatial and one space-time. We fund that in function of the video sequence, and more especially in function of the motion inside the sequence, the spatial or the space-time interest point detector is more or less relevant to predict eye movements

Planning Coverage of Points of Interest via Multiple Imaging Surveillance Assets: A Multi-Model Approach

For the United States to maintain information superiority, it is necessary to have a means of allocating intelligence-gathering assets to collect information on particular points of interest. In today\u27s geopolitical environment, however, the number of points of interest is growing rapidly, whereas the number of available assets is not. To aid in maintaining information superiority, this research explores the use of a Multi-Modal Goal Programming Resource Constrained Project Scheduling approach for allocating imaging surveillance assets (land, air, sea, and space) to a set of points of interest for a given time period. The multiple objectives of this formulation are to minimize the number of points of interest not covered at any time during the required period, minimize the deviation from the minimum image resolution of each point of interest, and minimize the time between successive imaging assets imaging each point of interest