When space points and camera optical center lie on a twisted cubic, no matter how many corresponding pairs there are from space points to their image points, camera projection matrix cannot be uniquely determined, in ...
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ISBN:
(纸本)3540312447
When space points and camera optical center lie on a twisted cubic, no matter how many corresponding pairs there are from space points to their image points, camera projection matrix cannot be uniquely determined, in other words, the configuration of camera and space points in this case is critical for camera parameter estimation. In practice, it is important to detect;this critical configuration before the estimated camera parameters are used. In this work, a new method is introduced to detect this critical configuration, which is based on an effective criterion function constructed from an invariant relationship between six space points and their corresponding image points. the advantage of this method is that no explicit computation on camera projection matrix or optical center is needed. Simulations show it is quite robust and stable against noise. Experiments on real data, show the criterion function can be faithfully trusted for camera parameter estimation.
this three-volume set LNCS 14406-14408 constitutes the refereed proceedings of the 7th Asian conference on patternrecognition, ACPR 2023, held in Kitakyushu, Japan, in November 2023. the 93 full papers presented were...
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ISBN:
(数字)9783031476655
ISBN:
(纸本)9783031476648
this three-volume set LNCS 14406-14408 constitutes the refereed proceedings of the 7th Asian conference on patternrecognition, ACPR 2023, held in Kitakyushu, Japan, in November 2023. the 93 full papers presented were carefully reviewed and selected from 164 submissions. the conference focuses on four important areas of patternrecognition: patternrecognition and machine learning, computervision and robot vision, signal processing, and media processing and interaction, covering various technical aspects.
this three-volume set LNCS 14406-14408 constitutes the refereed proceedings of the 7th Asian conference on patternrecognition, ACPR 2023, held in Kitakyushu, Japan, in November 2023. the 93 full papers presented were...
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ISBN:
(数字)9783031476341
ISBN:
(纸本)9783031476334
this three-volume set LNCS 14406-14408 constitutes the refereed proceedings of the 7th Asian conference on patternrecognition, ACPR 2023, held in Kitakyushu, Japan, in November 2023. the 93 full papers presented were carefully reviewed and selected from 164 submissions. the conference focuses on four important areas of patternrecognition: patternrecognition and machine learning, computervision and robot vision, signal processing, and media processing and interaction, covering various technical aspects.
this three-volume set LNCS 14406-14408 constitutes the refereed proceedings of the 7th Asian conference on patternrecognition, ACPR 2023, held in Kitakyushu, Japan, in November 2023. the 93 full papers presented were...
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ISBN:
(数字)9783031476372
ISBN:
(纸本)9783031476365
this three-volume set LNCS 14406-14408 constitutes the refereed proceedings of the 7th Asian conference on patternrecognition, ACPR 2023, held in Kitakyushu, Japan, in November 2023. the 93 full papers presented were carefully reviewed and selected from 164 submissions. the conference focuses on four important areas of patternrecognition: patternrecognition and machine learning, computervision and robot vision, signal processing, and media processing and interaction, covering various technical aspects.
Fashion is an increasingly important topic in computervision, in particular the so-called street-to-shop task of matching street images with shop images containing similar fashion items. Solving this problem promises...
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ISBN:
(纸本)9789897582769
Fashion is an increasingly important topic in computervision, in particular the so-called street-to-shop task of matching street images with shop images containing similar fashion items. Solving this problem promises new means of making fashion searchable and helping shoppers find the articles they are looking for. this paper focuses on finding pieces of clothing worn by a person in full-body or half-body images with neutral backgrounds. Such images are ubiquitous on the web and in fashion blogs, and are typically studio photos, we refer to this setting as studio-to-shop. Recent advances in computational fashion include the development of domain-specific numerical representations. Our model Studio2Shop builds on top of such representations and uses a deep convolutional network trained to match a query image to the numerical feature vectors of all the articles annotated in this image. Top-k retrieval evaluation on test query images shows that the correct items are most often found within a range that is sufficiently small for building realistic visual search engines for the studio-to-shop setting.
In recent years, the subject of detection of Lunar impact craters based on deep learning methods has been widely studied withthe aim of providing efficient and effective methods for the automatic detection of Lunar i...
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Stochastic grammar has been used in many video analysis and event recognition applications as an efficient model to represent large-scale video activity. However, in previous works, due to the limitation on representi...
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ISBN:
(纸本)3540312196
Stochastic grammar has been used in many video analysis and event recognition applications as an efficient model to represent large-scale video activity. However, in previous works, due to the limitation on representing parallel temporal relations, traditional stochastic grammar cannot be used to model complex multi-agent activity including parallel temporal relations between sub-activities (such as "during" relation). In this paper, we extend the traditional grammar by introducing Temporal Relation Events (TRE) to solve the problem. the corresponding grammar parser appending complex temporal inference is also proposed. A system that can recognize two hands' cooperative action in a "telephone calling" activity is built to demonstrate the effectiveness of our methods. In the experiment, a simple method to model the explicit state duration probability distribution in HMM detector is also proposed for accurate primitive events detection.
In this paper, we describe the probabilistic approach to solve Poisson equations and how this method may be used to solve computervision problems. We also give a complexity analysis of this method and compare our met...
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Temporal action localization for untrimmed videos is a difficult problem in computervision. It is challenge to infer the start and end of activity instances on small-scale datasets covering multi-view information acc...
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ISBN:
(数字)9781665487399
ISBN:
(纸本)9781665487399
Temporal action localization for untrimmed videos is a difficult problem in computervision. It is challenge to infer the start and end of activity instances on small-scale datasets covering multi-view information accurately. In this paper, we propose an effective activity temporal localization and classification method to localize the temporal boundaries and predict the class label of activities for naturalistic driving. Our approach includes (i) a distraction behavior recognition and localization method in naturalistic driving videos on small-scale data sets, (ii) a strategy that uses multi-branch network to make full use of information from different channels, (iii)a post-processing method for selecting and correcting temporal range to ensure that our system finds accurate boundaries. In addition, the frame-level object detection information is also utilized. Extensive experiments prove the effectiveness of our method and we rank the 6th on the Test-A2 of the 6th AI City Challenge track 3.
In this paper, we present a novel approach for the fully automated detection of faulty weft threads on airjet weaving machines using computervision. the proposed system consists of a camera array for image acquisitio...
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ISBN:
(纸本)9789897582769
In this paper, we present a novel approach for the fully automated detection of faulty weft threads on airjet weaving machines using computervision. the proposed system consists of a camera array for image acquisition and a classification pipeline in which we use different image processing and machine learning methods to allow precise localization and reliable classification of defects. the camera system is introduced and its advantages over other approaches are discussed. Subsequently, the processing steps are motivated and described in detail, followed by an in-depth analysis of the impact of different system parameters to allow chosing optimal algorithm combinations for the problem of faulty weft yarn detection. To analyze the capabilities of our solution, system performance is thoroughly evaluated under realistic production settings, showing excellent detection rates.
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