다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

The PASCAL Visual Object Classes Challenge

A morphable model for the synthesis of 3D faces

This survey aims at providing multimedia researchers with a state-of-the-art overview of fusion strategies, which are used for combining multiple modalities in order to accomplish various multimedia analysis tasks. The existing literature on multimodal fusion research is presented through several classifications based on the fusion methodology and the level of fusion (feature, decision, and hybrid). The fusion methods are described from the perspective of the basic concept, advantages, weaknesses, and their usage in various analysis tasks as reported in the literature. Moreover, several distinctive issues that influence a multimodal fusion process such as, the use of correlation and independence, confidence level, contextual information, synchronization between different modalities, and the optimal modality selection are also highlighted. Finally, we present the open issues for further research in the area of multimodal fusion.

/pdf/multimodal-fusion-for-multimedia-analysis-a-survey-5f9wxprbby.pdf

Multimodal fusion for multimedia analysis: a survey

Gabor features have been extensively used for facial image analysis due to their powerful representation capabilities. This paper focuses on selecting and combining multiple Gabor classifiers that are trained on, for example, different scales and local regions. The system exploits curvature Gabor features in addition to conventional Gabor features. Final classifier is obtained by combining selected classifiers using Sequential Forward Floating Search-based selection mechanism. In addition, we combine classifiers trained on different local representations at score-level by learning the weights with partial least square regression. The system is evaluated on Face Recognition Grand Challenge (FRGC) version 2.0 Experiment 4. The proposed system achieves 94.16% verification rate @ 0.1% FAR, which is the highest accuracy reported on this experiment so far in the literature.

/pdf/selection-and-combination-of-local-gabor-classifiers-for-2fanqo9dge.pdf

Selection and combination of local Gabor classifiers for robust face verification

Universität Karlsruhe (TH) at TRECVID 2008.

Facial analysis based on local regions/blocks usually outperforms holistic approaches because it is less sensitive to local deformations and occlusions. Moreover, modeling local features enables us to avoid the problem of high dimensionality of feature space. In this paper, we model the local face blocks with Gabor features and project them into a discriminant identity space. The similarity score of a face pair is determined by fusion of the local classifiers. To acquire complementary information in different scales of face images, we integrate the local decisions from various image resolutions. The proposed multi-resolution block based face verification system is evaluated on the experiment 4 of Face Recognition Grand Challenge (FRGC) version 2.0. We obtained 92.5% verification rate@0.1% FAR, which is the highest performance reported on this experiment so far in the literature.

/pdf/multi-resolution-local-appearance-based-face-verification-3tcz2m5cmg.pdf

Multi-resolution Local Appearance-Based Face Verification

Magic Mirror is a face swapping tool that replaces the user's face with a selected famous person's face in the database. System interacts with the user via a user interface which enables the selection of the replacement face and directly reflects the changed appearance. First, we apply a face detection mechanism to locate the face in the frame coming from the capturing device. Then, we feed the detection result to an active appearance model to get the exact shape of the face. By using extracted information, we replace the user's face with selected target face.We display output after some post processing for color and lighting adjustments.

/pdf/real-time-face-swapping-in-video-sequences-magic-mirror-261qaukvrl.pdf

Real-time face swapping in video sequences: Magic Mirror

Acquiring knowledge about persons is a key functionality for humanoid robots. By envisioning a robot that can provide personalized services the system needs to detect, recognize and memorize information about specific persons. To reach this goal we present an approach for extensible person identification based on visual processing, as one com- ponent of an interactive system able to interactively acquire information about persons. This paper describes an approach for face-ID recognition and identifica- tion over image sequences and its integration into the interactive system. We compare the approach of sequence hypotheses against results from single image hypotheses, and a standard approach and show improve- ments in both cases. We furthermore explore the usage of confidence scores to allow other system components to estimate the accuracy of face-ID hypotheses.

Hazim Kemal Ekenel

Papers

Selection and combination of local Gabor classifiers for robust face verification

Universität Karlsruhe (TH) at TRECVID 2008.

Multi-resolution Local Appearance-Based Face Verification

Real-time face swapping in video sequences: Magic Mirror

Integrating Face-ID into an Interactive Person-ID Learning System