the proceedings contain 74 papers. the special focus in this conference is on Tracking, Segmentation, 3D Shape and Optical Flow. the topics include: Multimodal shape tracking with point distribution models;on optimal ...
ISBN:
(纸本)354044209X
the proceedings contain 74 papers. the special focus in this conference is on Tracking, Segmentation, 3D Shape and Optical Flow. the topics include: Multimodal shape tracking with point distribution models;on optimal camera parameter selection in kalman filter based object tracking;video-based handsign recognition for intuitive human-computer-interaction;quality enhancement of reconstructed 3d models using coplanarity and constraints;human body reconstruction from image sequences;a knowledge-based system for context dependent evaluation of remote sensing data;empirically convergent adaptive estimation of grayvalue structure tensors;fast ICP algorithms for shape registration;appearance based generic object modeling and recognition using probabilistic principal component analysis;logarithmic tapering graph pyramid;a new and efficient algorithm for detecting the corners in digital images;unsupervised image partitioning with semidefinite programming;the application of genetic algorithms in structural seismic image interpretation;efficient modification of the central weighted vector median filter;fast recovery of piled deformable objects using superquadrics;analysis of amperometric biosensor curves using hidden-Markov-modells;unifying registration and segmentation for multi-sensor images;relations between soft wavelet shrinkage and total variation denoising;statistical image sequence processing for temporal change detection;shape from single stripe pattern illumination;a probabilistic approach to building roof reconstruction using semantic labelling;adaptive pose estimation for different corresponding entities;properties of a three-dimensional island hierarchy for segmentation of 3d images withthe color structure code and hierarchical primitives based contour matching.
the proceedings contain 25 papers. the topics discussed include: accurate extraction of line-structured optical stripe centerlines under low exposure;research on grid inspection technology based on general knowledge e...
ISBN:
(纸本)9781510674950
the proceedings contain 25 papers. the topics discussed include: accurate extraction of line-structured optical stripe centerlines under low exposure;research on grid inspection technology based on general knowledge enhanced multi-modal large language models;a comparison between deep-learning models for scene recognition;binary network design for dedicated hardware circuits;evaluation of training datasets for typical target detection networks;optimal exposure selection of high dynamic range-based reflection compensation for printed circuit board reconstruction using structured light 3D measurement system;fall detection model based on Alphapose combined with LSTM and Lightgbm;and an image enhancement algorithm based on multi-scale Retinex theory to improve the images quality of sensors.
A deformable shape model called Active Shape Structural Model (ASSM) is used within a biometric framework to define a biometric sketch recognition algorithm. Experimental results show that mainly structural relations ...
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ISBN:
(纸本)3540408614
A deformable shape model called Active Shape Structural Model (ASSM) is used within a biometric framework to define a biometric sketch recognition algorithm. Experimental results show that mainly structural relations rather than statistical features can be used to recognize sketches of different users with high accuracy.
A novel, fast feature selection method for hidden Markov model (HMM) based classifiers is introduced in this paper. It is also shown how this method can be used to create ensembles of classifiers. the proposed methods...
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ISBN:
(纸本)3540408614
A novel, fast feature selection method for hidden Markov model (HMM) based classifiers is introduced in this paper. It is also shown how this method can be used to create ensembles of classifiers. the proposed methods are tested in the context of a handwritten text recognition task.
Rotation-invariant texture features are generated by randomizing the orientation of the underlying texture operators. the approach is applied to texture features based on local binary patterns aswell as to sum and dif...
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ISBN:
(纸本)3540408614
Rotation-invariant texture features are generated by randomizing the orientation of the underlying texture operators. the approach is applied to texture features based on local binary patterns aswell as to sum and difference histograms. Results are given for a difficult classification problem of 15 different Brodatz textures and 7 rotation angles. Due to randomization, the error rate becomes independent of the texture orientation. Moreover, the classification of periodic textures is enhanced significantly.
Methods for the recognition of multiple objects in images using local representations are introduced. Starting from a straight forward approach, we combine the use of local representations with region segmentation and...
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ISBN:
(纸本)3540408614
Methods for the recognition of multiple objects in images using local representations are introduced. Starting from a straight forward approach, we combine the use of local representations with region segmentation and template matching. the performance of the classifiers is evaluated on four image databases of different difficulties. All databases consist of images containing one, two or three objects and differ in the backgrounds which are used. Also, the presence or absence of occlusions of the objects in the scenes is considered. Classification results are promising regarding the difficulty of the task.
the classification of bioacoustic time series is topic of this paper. In particular, we discuss the combination of local classifier decisions from several feature spaces with static and adaptable fusion schemes, e.g. ...
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ISBN:
(纸本)3540408614
the classification of bioacoustic time series is topic of this paper. In particular, we discuss the combination of local classifier decisions from several feature spaces with static and adaptable fusion schemes, e.g. averaging, voting and decision templates. We present static fusion schemes and algorithms to calculate decision templates, and demonstrate the behaviour of both approaches to bioacoustic applications, the classification of insect songs. Results of these algorithms are presented for species of crickets and katydids. Both families are members of the insect order Orthoptera.
A new direction in improving modern dialogue systems is to make a human-machine dialogue more similar to a human-human dialogue. this can be done by adding more input modalities, e.g. facial expression recognition. A ...
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ISBN:
(纸本)3540408614
A new direction in improving modern dialogue systems is to make a human-machine dialogue more similar to a human-human dialogue. this can be done by adding more input modalities, e.g. facial expression recognition. A common problem in a human-machine dialogue where the angry face may give a clue is the recurrent misunderstanding of the user by the system. this paper describes recognizing facial expressions in frontal images using eigenspaces. For the classification of facial expressions, rather than using the whole image we classify regions which do not differ between subjects and at the same time are meaningful for facial expressions. Using this face mask for training and classification of joy and anger expressions of the face, we achieved an improvement of up to 11% absolute. the portability to other classification problems is shown by a gender classification.
Accurately detecting craters in remotely sensed images is an important task when analysing the properties of planetary bodies. Commonly, only large craters in the range of several kilometres are detected. In this work...
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ISBN:
(纸本)9781728188089
Accurately detecting craters in remotely sensed images is an important task when analysing the properties of planetary bodies. Commonly, only large craters in the range of several kilometres are detected. In this work we provide the first example of automatically detecting tiny craters in the range of several meters withthe help of a deep neural network by using only a small set of annotated craters. Additionally, we propose a novel way to group overlapping detections and replace the commonly used non-maximum suppression with a probabilistic treatment. As a result, we receive valuable uncertainty estimates of the detections and the aggregated detections are shown to be vastly superior.
We present a holistic statistical model for the automatic analysis of complex scenes. Here, holistic refers to an integrated approach that does not take local decisions about segmentation or object transformations. St...
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ISBN:
(纸本)3540408614
We present a holistic statistical model for the automatic analysis of complex scenes. Here, holistic refers to an integrated approach that does not take local decisions about segmentation or object transformations. Starting from Bayes' decision rule, we develop an appearance-based approach explaining all pixels in the given scene using an explicit background model. this allows the training of object references from unsegmented data and recognition of complex scenes. We present empirical results on different databases obtaining state-of-the-art results on two databases where a comparison to other methods is possible. To obtain quantifiable results for object-based recognition, we introduce a new database with subsets of different difficulties.
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