Proceedings ArticleDOI
Face sketch recognition system: A content based image retrieval approach
Salah Eddine Lahlali,Abdelalim Sadiq,Samir Mbarki +2 more
- pp 428-433
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TLDR
A new use of CBIR approach is presented in an important application that can assist law enforcement in solving many complicated crimes by matching forensic sketch with digital human face or face sketch recognition system.Abstract:
Content Based Image Retrieval has been one of the most popular topics in the computer vision literature. CBIR offers the opportunity to research from a huge multimedia database and with appropriate methods the relevant collections of images that have characteristics similar to the case(s) of interest. In the forensic field, CBIR has many possible uses in crime fighting and has also been investigated as a potential image-based search technology. This paper presents a new use of CBIR approach in an important application that can assist law enforcement in solving many complicated crimes. It is matching forensic sketch with digital human face or face sketch recognition system.read more
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Journal Article
Inter-modality Face Recognition
Dahua Lin,Xiaoou Tang +1 more
TL;DR: Wang et al. as mentioned in this paper proposed a Common Discriminant Feature Extraction (CDFE) algorithm for inter-modality face recognition, where two transforms are simultaneously learned to transform the samples in both modalities respectively to the common feature space.
References
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Journal ArticleDOI
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: The Scale-Invariant Feature Transform (or SIFT) algorithm is a highly robust method to extract and consequently match distinctive invariant features from images that can then be used to reliably match objects in diering images.
Journal ArticleDOI
Face Description with Local Binary Patterns: Application to Face Recognition
TL;DR: This paper presents a novel and efficient facial image representation based on local binary pattern (LBP) texture features that is assessed in the face recognition problem under different challenges.
Journal ArticleDOI
The FERET evaluation methodology for face-recognition algorithms
TL;DR: Two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems.