TOWARDS GESTURE-BASED MULTI-USER INTERACTIONS IN COLLABORATIVE VIRTUAL ENVIRONMENTS

We present a virtual reality (VR) setup that enables multiple users to participate in collaborative virtual environments and interact via gestures. A collaborative VR session is established through a network of users that is composed of a server and a set of clients. The server manages the communication amongst clients and is created by one of the users. Each user's VR setup consists of a Head Mounted Display (HMD) for immersive visualisation, a hand tracking system to interact with virtual objects and a single-hand joypad to move in the virtual environment. We use Google Cardboard as a HMD for the VR experience and a Leap Motion for hand tracking, thus making our solution low cost. We evaluate our VR setup though a forensics use case, where real-world objects pertaining to a simulated crime scene are included in a VR environment, acquired using a smartphone-based 3D reconstruction pipeline. Users can interact using virtual gesture-based tools such as pointers and rulers

Multi-view data capture for dynamic object reconstruction using handheld augmented reality mobiles

We propose a system to capture nearly-synchronous frame streams from multiple and moving handheld mobiles that is suitable for dynamic object 3D reconstruction. Each mobile executes Simultaneous Localisation and Mapping on-board to estimate its pose, and uses a wireless communication channel to send or receive synchronisation triggers. Our system can harvest frames and mobile poses in real time using a decentralised triggering strategy and a data-relay architecture that can be deployed either at the Edge or in the Cloud. We show the effectiveness of our system by employing it for 3D skeleton and volumetric reconstructions. Our triggering strategy achieves equal performance to that of an NTP-based synchronisation approach, but offers higher flexibility, as it can be adjusted online based on application needs. We created a challenging new dataset, namely 4DM, that involves six handheld augmented reality mobiles recording an actor performing sports actions outdoors. We validate our system on 4DM, analyse its strengths and limitations, and compare its modules with alternative ones.Comment: Accepted in Journal of Real-Time Image Processin

Support Vector Motion Clustering

This work was supported in part by the Erasmus Mundus Joint Doctorate in Interactive and Cognitive Environments (which is funded by the EACEA Agency of the European Commission under EMJD ICE FPA n 2010-0012) and by the Artemis JU and the UK Technology Strategy Board through COPCAMS Project under Grant 332913

A method for performance diagnosis and evaluation of video trackers

Several measures for evaluating multi-target video trackers exist that generally aim at providing ‘end performance.’ End performance is important particularly for ranking and comparing trackers. However, for a deeper insight into trackers’ performance it would also be desirable to analyze key contributory factors (false positives, false negatives, ID changes) that (implicitly or explicitly) lead to the attainment of a certain end performance. Specifically, this paper proposes a new approach to enable a diagnosis of the performance of multi-target trackers as well as providing a means to determine the end performance to still enable their comparison in a video sequence. Diagnosis involves analyzing probability density functions of false positives, false negatives and ID changes of trackers in a sequence. End performance is obtained in terms of the extracted performance scores related to false positives, false negatives and ID changes. In the experiments, we used four state-of-the-art trackers on challenging real-world public datasets to show the effectiveness of the proposed approach

New Binding Mode to TNF-Alpha Revealed by Ubiquitin-Based Artificial Binding Protein

A variety of approaches have been employed to generate binding proteins from non-antibody scaffolds. Utilizing a beta-sheet of the human ubiquitin for paratope creation we obtained binding proteins against tumor necrosis factor (TNF)-alpha. The bioactive form of this validated pharmacological target protein is a non-covalently linked homo-trimer. This structural feature leads to the observation of a certain heterogeneity concerning the binding mode of TNF-alpha binding molecules, for instance in terms of monomer/trimer specificity. We analyzed a ubiquitin-based TNF-alpha binder, selected by ribosome display, with a particular focus on its mode of interaction. Using enzyme-linked immunosorbent assays, specific binding to TNF-alpha with nanomolar affinity was observed. In isothermal titration calorimetry we obtained comparable results regarding the affinity and detected an exothermic reaction with one ubiquitin-derived binding molecule binding one TNF-alpha trimer. Using NMR spectroscopy and other analytical methods the 1∶3 stoichiometry could be confirmed. Detailed binding analysis showed that the interaction is affected by the detergent Tween-20. Previously, this phenomenon was reported only for one other type of alternative scaffold-derived binding proteins – designed ankyrin repeat proteins – without further investigation. As demonstrated by size exclusion chromatography and NMR spectroscopy, the presence of the detergent increases the association rate significantly. Since the special architecture of TNF-alpha is known to be modulated by detergents, the access to the recognized epitope is indicated to be restricted by conformational transitions within the target protein. Our results suggest that the ubiquitin-derived binding protein targets a new epitope on TNF-alpha, which differs from the epitopes recognized by TNF-alpha neutralizing antibodies

Supervised framework for automatic recognition and retrieval of interaction: a framework for classification and retrieving videos with similar human interactions

This study presents supervised framework for automatic recognition and retrieval of interactions (SAFARRIs), a supervised learning framework to recognise interactions such as pushing, punching, and hugging, between a pair of human performers in a video shot. The primary contribution of the study is to extend the vectors of locally aggregated descriptors (VLADs) as a compact and discriminative video encoding representation, to solve the complex class partitioning problem of recognising human interaction. An initial codebook is generated from the training set of video shots, by extracting feature descriptors around the spatiotemporal interest points computed across frames. A bag of action words is generated by encoding the first‐order statistics of the visual words using VLAD. Support vector machine classifiers (1 against all) are trained using these codebooks. The authors have verified SAFARRI's accuracy for classification and retrieval (query by example). SAFARRI is free from tracking or recognition of body parts and capable of identifying the region of interaction in video shots. It gives superior retrieval and classification performances over recently proposed methods, on two publicly available human interaction datasets

Online multi-target tracking with strong and weak detections

none3We propose an online multi-target tracker that exploits both high- and low-confidence target detections in a Probability Hypothesis Density Particle Filter framework. High-confidence (strong) detections are used for label propagation and target initialization. Low-confidence (weak) detections only support the propagation of labels, i.e. tracking existing targets. Moreover, we perform data association just after the prediction stage thus avoiding the need for computationally expensive labeling procedures such as clustering. Finally, we perform sampling by considering the perspective distortion in the target observations. The tracker runs on average at 12 frames per second. Results show that our method outperforms alternative online trackers on the Multiple Object Tracking 2016 and 2015 benchmark datasets in terms tracking accuracy, false negatives and speed.noneSanchez-Matilla, R.; Poiesi, F.; Cavallaro, A.Sanchez-Matilla, R.; Poiesi, F.; Cavallaro, A

3DNOW: Image-based 3D reconstruction and modeling via web

This paper presents a web-based 3D imaging pipeline, namely 3Dnow, that can be used by anyone without the need of installing additional software other than a browser. By uploading a set of images through the web interface, 3Dnow can generate sparse and dense point clouds as well as mesh models. 3D reconstructed models can be downloaded with standard formats or previewed directly on the web browser through an embedded visualisation interface. In addition to reconstructing objects, 3Dnow offers the possibility to evaluate and georeference point clouds. Reconstruction statistics, such as minimum, maximum and average intersection angles, point redundancy and density can also be accessed. The paper describes all features available in the web service and provides an analysis of the computational performance using servers with different GPU configurations

Capillary electrophoresis for the investigation of illicit drugs in hair: determination of cocaine and morphine

Toxicological analysis of hair is becoming a popular method for investigating past, chronic use of illicit drugs. Several analytical methods using immunometry, chromatography and mass spectrometry have been reported. In this work, capillary electrophoresis was first used for the determination of illicit drugs, such as cocaine and morphine, in the hair of heroin and cocaine users. After rapid washing, hair samples were incubated overnight in 0.25 M HCl at 45 degrees C and the mixtures were extracted with ready-to-use Toxi-tubes A. The organic phase was evaporated and the residue dissolved in a suitable amount of electrophoresis buffer. Free zone capillary electrophoretic determinations of morphine, the main heroin metabolite, and cocaine were accomplished in 0.05 M borate buffer (pH 9.2) at a potential of 15,000 V, with UV detection at 214 and 238 nm, respectively. The use of the less selective wavelength of 200 nm allowed the simultaneous detection of both compounds. Efficient separations (up to 350,000 theoretical plates) and accurate and precise determinations (intra-day R.S.D.s in the range 3-5%) of cocaine and morphine in hair extracts were easily achieved. The analytical sensitivity was sufficient to determinate as little as 0.15 ng/mg of cocaine and morphine in hair using 100-mg samples. Interferences from more than 90 therapeutic drugs and drugs of abuse were excluded