Image-based face retrieval in online dating profile search

14.05.2017

image-based face retrieval in online dating profile search

Email RSS Save to Binder Export Formats: Occlusion or damage in facial portions will bring a remarkable discomfort and information loss. The search includes comparing a query image provided by the user to a plurality dota 2 matchmaking finding server stored images of faces stored in a stored image database, and determining a similarity of the query image to the plurality of stored images. Comparative saerch of simple facial features extractors. In the figures, the left-most digit of a reference number identifies the figure in which the designated component or act first appears. By way of example and not limitation, the image-based search described herein may be employed in social research applications, advertising, social networks, media production, and the like. The papers are organized in topical sections on audio, image video processing, coding and compression; media content browsing and retrieval; multi-camera, multi-view, and 3D systems; multimedia indexing and mining; imave-based content analysis; multimedia signal processing and communications; and multimedia applications. However, any other way of indicating a user's preference for one facial feature over another feature may additionally or alternatively be used. This application is a continuation of and claims priority to U. One or more resultant images of faces, selected from among the stored images, are displayed to the user based on the determined similarity of the stored images to the query image. Tools and Resources Buy this Article Datjng the ACM DL to your organization TOC Service: Users of the dating services typically create a profile, including a textual description and one or more pictures of the user. PDF Get this Article. To search image-based face retrieval in online dating profile search images of faces similar to a query image, a user provides a copy of the query image.

Do image-based face retrieval in online dating profile search want to read the image-based face retrieval in online dating profile search of this conference paper? Here are the instructions how to enable JavaScript in your web browser. Textual search, the approach used by the majority of existing online dating sites, successfully covers a variety of attributes, such as age range and gender, but falls short when searching for facial features. Meanwhile, by using images as the query in a search, current image-based face-retrieval applications ease the challenge of textual description from users, but only focus on finding the same person.

We believe there is a gap that needs to be filled in image-based face retrieval to further support the interpersonal search scenarios on Internet dating sites. Therefore, we are introducing a profile search pprofile -- ImLooking inline using an augmented image-based face retrieval filter. First, we present a prototype design and offer technical support. In a user study, participants quickly felt at home in user interface and acclimatized to the way the prototype operates. In addition, they reported they enjoyed the image-based face retrieval in online dating profile search process.

Citations Citations 6 References References A Novel Metrics Based on Information Bottleneck Principle for Face Retrieval. In this paper, we propose a novel metrics for statistical features of images based on Information Bottleneck principle IBP. Rather than measure the differences among images with classical distance, our model takes the attributes of feature space into consideration.

Through evaluating the loss of information of image database, our model is especially designed for the type of features bearing statistical attributes such as histograms, moments etc. The statistical feature is adopted to denote the information of the image database and our metrics measures the distance between two images with the amount of decreased information due to combine them as one category.

The proposed metrics is validated in face retrieval with the dominant Local Binary Pattern LBP feature. Experimental results on FERET face database show that our model possesses preferable performance. Qiyun Cai Yuchun Fang Jie Luo Wang Dai Wang Dai. Patch-guided facial image inpainting by shape propagation. Images with human faces comprise an essential part in the imaging realm. Occlusion or damage in facial portions will bring a remarkable discomfort and information loss.

Inpainting is a set of image processing methods to recover missing image portions. We extend the image inpainting methods by introducing facial domain knowledge. With the support of a face retrkeval, our approach propagates structural information, i. Using the inferred structural information as guidance, an exemplar-based image inpainting algorithm is employed to copy patches in the same face from the source portion to the missing portion.

This newly proposed concept of facial image inpainting outperforms the traditional inpainting methods by propagating the facial shapes from a face database, fxce avoids the problem of variations in imaging conditions from different images by inferring colors and textures from the same face image. Our system produces seamless faces that are hardly seen drawbacks.

Yue-ting Retrkeval Yu-shun Wang Timothy K. ABSTRACT Digital photo management,is becoming,indispensable for the explosively growing family photo albums due to the rapid popularization of digital cameras and mobile phone cameras. In an effective photo management,system photo annotation is the most challenging task. In this paper, we develop several innovative interaction techniques for semi-automatic photo annotation.

Compared with traditional annotation systems, our approach provides the following new features: Our results show that these technologies provide a more user friendly interface for the annotation of person name, location, and event, and thus onlins improve the annotation performance,especially for a large photo album. ACM Classification Keywords H. Comparative analysis of simple facial features extractors.

In the article a certain class of feature extractors for face recognition is presented. The extraction is based on simple approaches: The experiments performed on vating facial image databases BioID [4], ORL face database [27], FERET on,ine show that face recognition using this class of extractors is particularly efficient and fast, and can have straightforward implementations in software and hardware systems.

They can also be used in fast face recognition system involving feature-integration, as well as a tool for similar faces retrieval in 2-tier systems as initial processing, before exact face recognition. A Pivot-Based Distributed Pseudo Facial Image Retrieval in Manifold Spaces: The research of cognitive science indicates that manifold-learning-based facial image retrieval is based on human perception, which can accurately capture the intrinsic similarity of two facial images.

The paper proposes a pivot-based Distributed Pseudo Serach Retrieval method called DPSR in manifold spaces with the aid of a adjacency distance list ADL. Specifically, we first construct a two dimensional array, called ADL which records the pair-wise distance between any two facial images with a constraint in the database. Extensive experimental studies show that the DPSR outperforms the conventional sequential scan in manifold spaces by a large margin, especially for the large high-dimensional datasets.

A Bi-objective Optimization Model for Interactive Face Retrieval. In this paper, based on Bayesian relevance feedback methods, we propose a novel interactive face retrieving model based on two objective functions, one is the Maximum a Posterior MAP and the other is maximization of mutual information. The proposed bi-objective optimization model aims at minimizing both the number of interactive iterations and the average length of iterations.

Moreover, we deduce a top-bottom search algorithm to solve the proposed. Experiments with real testers prove that the proposed algorithm could largely improve the interactive searching efficiency in face databases.

us asian dating sites. dating websites free in australia dating math age hookup and commissioning manager latest free usa dating sites. Vícejazyčný online slovník. Překlady z češtiny do angličtiny, francouzštiny, němčiny, španělštiny, italštiny, ruštiny, slovenštiny a naopak. Yuen, P.C., Man, C.H.: Human Face Image Searching System Using Sketches. X.: Imlooking: Image - based Face Retrieval in Online Dating Profile Search. Instead of directly measure the difference between two images, we build a feature X.: Imlooking: image - based face retrieval in online dating profile search.