738 research outputs found

    Visual Object Tracking in First Person Vision

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    The understanding of human-object interactions is fundamental in First Person Vision (FPV). Visual tracking algorithms which follow the objects manipulated by the camera wearer can provide useful information to effectively model such interactions. In the last years, the computer vision community has significantly improved the performance of tracking algorithms for a large variety of target objects and scenarios. Despite a few previous attempts to exploit trackers in the FPV domain, a methodical analysis of the performance of state-of-the-art trackers is still missing. This research gap raises the question of whether current solutions can be used “off-the-shelf” or more domain-specific investigations should be carried out. This paper aims to provide answers to such questions. We present the first systematic investigation of single object tracking in FPV. Our study extensively analyses the performance of 42 algorithms including generic object trackers and baseline FPV-specific trackers. The analysis is carried out by focusing on different aspects of the FPV setting, introducing new performance measures, and in relation to FPV-specific tasks. The study is made possible through the introduction of TREK-150, a novel benchmark dataset composed of 150 densely annotated video sequences. Our results show that object tracking in FPV poses new challenges to current visual trackers. We highlight the factors causing such behavior and point out possible research directions. Despite their difficulties, we prove that trackers bring benefits to FPV downstream tasks requiring short-term object tracking. We expect that generic object tracking will gain popularity in FPV as new and FPV-specific methodologies are investigated

    Bronchial to subclavian shunt in a CF patient. A potential pitfall for embolization

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    Bronchial artery embolization is a well accepted and widely used technique in the management of massive haemoptysis in cystic fibrosis (CF). It can be a complex procedure requiring a deep knowledge of the bronchial artery anatomy including the possible bronchial anastomoses. We report a case of complex vascular anatomy of the left bronchial artery with multiple anastomoses with the ipsilateral subclavian artery as cause of non-attempted embolization. \ua9 2003 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved

    Concettualizzazione e contestualizzazione dei beni culturali archeologici

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    This report describes the observations made while developing a new methodology for historic surveys used for the re-contextualisation of archaeological finds. This particular methodology avails itself of both traditional historic surveys as well as the representation of knowledge through ontology. The methodology described here was developed in reference to specific cases of re-contextualisation of archaeological artefacts from Pompeii which are now in the National Archaeological Museum in Naples

    The efficacy of epidermal growth factor receptor-specific antibodies against glioma xenografts is influenced by receptor levels, activation status, and heterodimerization

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    Purpose: Factors affecting the efficacy of therapeutic monoclonal antibodies (mAb) directed to the epidermal growth factor receptor (EGFR) remain relatively unknown, especially in glioma. Experimental Design: We examined the efficacy of two EGFR-specific mAbs (mAbs 806 and 528) against U87MG-derived glioma xenografts expressing EGFR variants. Using this approach allowed us to change the form of the EGFR while keeping the genetic background constant. These variants included the de2-7 EGFR (or EGFRvIII), a constitutively active mutation of the EGFR expressed in glioma. Results: The efficacy of the mAbs correlated with EGFR number; however, the most important factor was receptor activation. Whereas U87MG xenografts expressing the de2-7 EGFR responded to therapy, those exhibiting a dead kinase de2-7 EGFR were refractory. A modified de2-7 EGFR that was kinase active but autophosphorylation deficient also responded, suggesting that these mAbs function in de2-7 EGFR–expressing xenografts by blocking transphosphorylation. Because de2-7 EGFR–expressing U87MG xenografts coexpress the wild-type EGFR, efficacy of the mAbs was also tested against NR6 xenografts that expressed the de2-7 EGFR in isolation. Whereas mAb 806 displayed antitumor activity against NR6 xenografts, mAb 528 therapy was ineffective, suggesting that mAb 528 mediates its antitumor activity by disrupting interactions between the de2-7 and wild-type EGFR. Finally, genetic disruption of Src in U87MG xenografts expressing the de2-7 EGFR dramatically enhanced mAb 806 efficacy. Conclusions: The effective use of EGFR-specific antibodies in glioma will depend on identifying tumors with activated EGFR. The combination of EGFR and Src inhibitors may be an effective strategy for the treatment of glioma

    Forecasting Human-Object Interaction: Joint Prediction of Motor Attention and Actions in First Person Video

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    We address the challenging task of anticipating human-object interaction in first person videos. Most existing methods ignore how the camera wearer interacts with the objects, or simply consider body motion as a separate modality. In contrast, we observe that the international hand movement reveals critical information about the future activity. Motivated by this, we adopt intentional hand movement as a future representation and propose a novel deep network that jointly models and predicts the egocentric hand motion, interaction hotspots and future action. Specifically, we consider the future hand motion as the motor attention, and model this attention using latent variables in our deep model. The predicted motor attention is further used to characterise the discriminative spatial-temporal visual features for predicting actions and interaction hotspots. We present extensive experiments demonstrating the benefit of the proposed joint model. Importantly, our model produces new state-of-the-art results for action anticipation on both EGTEA Gaze+ and the EPIC-Kitchens datasets. Our project page is available at https://aptx4869lm.github.io/ForecastingHOI
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