Improving the Accuracy of Action Classification Using View-Dependent Context Information

Proceedings of: 6th International Conference, HAIS 2011, Wroclaw, Poland, May 23-25, 2011This paper presents a human action recognition system that decomposes the task in two subtasks. First, a view-independent classifier, shared between the multiple views to analyze, is applied to obtain an initial guess of the posterior distribution of the performed action. Then, this posterior distribution is combined with view based knowledge to improve the action classification. This allows to reuse the view-independent component when a new view has to be analyzed, needing to only specify the view dependent knowledge. An example of the application of the system into an smart home domain is discussed.This work was supported in part by Projects CICYT TIN2008-06742-C02-02/ TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/ TIC-1485) and DPS2008-07029-C02-02.Publicad

Wave Functions, Quantum Diffusion, and Scaling Exponents in Golden-Mean Quasiperiodic Tilings

We study the properties of wave functions and the wave-packet dynamics in quasiperiodic tight-binding models in one, two, and three dimensions. The atoms in the one-dimensional quasiperiodic chains are coupled by weak and strong bonds aligned according to the Fibonacci sequence. The associated d-dimensional quasiperiodic tilings are constructed from the direct product of d such chains, which yields either the hypercubic tiling or the labyrinth tiling. This approach allows us to consider rather large systems numerically. We show that the wave functions of the system are multifractal and that their properties can be related to the structure of the system in the regime of strong quasiperiodic modulation by a renormalization group (RG) approach. We also study the dynamics of wave packets to get information about the electronic transport properties. In particular, we investigate the scaling behaviour of the return probability of the wave packet with time. Applying again the RG approach we show that in the regime of strong quasiperiodic modulation the return probability is governed by the underlying quasiperiodic structure. Further, we also discuss lower bounds for the scaling exponent of the width of the wave packet and propose a modified lower bound for the absolute continuous regime.Comment: 25 pages, 13 figure

View-invariant action recognition

Human action recognition is an important problem in computer vision. It has a wide range of applications in surveillance, human-computer interaction, augmented reality, video indexing, and retrieval. The varying pattern of spatio-temporal appearance generated by human action is key for identifying the performed action. We have seen a lot of research exploring this dynamics of spatio-temporal appearance for learning a visual representation of human actions. However, most of the research in action recognition is focused on some common viewpoints, and these approaches do not perform well when there is a change in viewpoint. Human actions are performed in a 3-dimensional environment and are projected to a 2-dimensional space when captured as a video from a given viewpoint. Therefore, an action will have a different spatio-temporal appearance from different viewpoints. The research in view-invariant action recognition addresses this problem and focuses on recognizing human actions from unseen viewpoints

Fusion of Single View Soft k-NN Classifiers for Multicamera Human Action Recognition

Proceedings of: 5th International Conference on Hybrid Artificial Intelligence Systems (HAIS 2010). San Sebastián, Spain, June 23-25, 2010This paper presents two different classifier fusion algorithms applied in the domain of Human Action Recognition from video. A set of cameras observes a person performing an action from a predefined set. For each camera view a 2D descriptor is computed and a posterior on the performed activity is obtained using a soft classifier. These posteriors are combined using voting and a bayesian network to obtain a single belief measure to use for the final decision on the performed action. Experiments are conducted with different low level frame descriptors on the IXMAS dataset, achieving results comparable to state of the art 3D proposals, but only performing 2D processing.This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485) and DPS2008-07029-C02-02Publicad

Human Action Recognition Based on Temporal Pyramid of Key Poses Using RGB-D Sensors

Human action recognition is a hot research topic in computer vision, mainly due to the high number of related applications, such as surveillance, human computer interaction, or assisted living. Low cost RGB-D sensors have been extensively used in this field. They can provide skeleton joints, which represent a compact and effective representation of the human posture. This work proposes an algorithm for human action recognition where the features are computed from skeleton joints. A sequence of skeleton features is represented as a set of key poses, from which histograms are extracted. The temporal structure of the sequence is kept using a temporal pyramid of key poses. Finally, a multi-class SVM performs the classification task. The algorithm optimization through evolutionary computation allows to reach results comparable to the state-of-the-art on the MSR Action3D dataset.This work was supported by a STSM Grant from COST Action IC1303 AAPELE - Architectures, Algorithms and Platforms for Enhanced Living Environments

Multicamera Action Recognition with Canonical Correlation Analysis and Discriminative Sequence Classification

Proceedings of: 4th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011, La Palma, Canary Islands, Spain, May 30 - June 3, 2011.This paper presents a feature fusion approach to the recognition of human actions from multiple cameras that avoids the computation of the 3D visual hull. Action descriptors are extracted for each one of the camera views available and projected into a common subspace that maximizes the correlation between each one of the components of the projections. That common subspace is learned using Probabilistic Canonical Correlation Analysis. The action classification is made in that subspace using a discriminative classifier. Results of the proposed method are shown for the classification of the IXMAS dataset.Publicad

Fabrication of glass sphere laser fusion targets

We have developed processes at LLL for mass producing the high quality glass microspheres required for current laser fusion targets. Here we describe the methods and the materials used in our liquid-droplet and dried-gel systems. Glass microspheres ranging from 70 to 600 microns O.D., with walls from 0.5 to 18 microns thick and which satisfy the exacting surface and symmetry specifications of targets for high density experiments are now produced routinely

A Very Low-Carbohydrate Diet Improves Symptoms and Quality of Life in Diarrhea-Predominant Irritable Bowel Syndrome

Patients with diarrhea-predominant IBS (IBS-D) anecdotally report symptom improvement after initiating a very low-carbohydrate diet (VLCD). This is the first study to prospectively evaluate a VLCD in IBS-D