Topic
Sketch recognition
About: Sketch recognition is a research topic. Over the lifetime, 1611 publications have been published within this topic receiving 40284 citations.
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25 Aug 2019
TL;DR: Deep learning techniques used in face recognition and matching are focused on which as improved the accuracy of face recognition technique with training of huge sets of data.
Abstract: Considering the existence of very large amount of available data repositories and reach to the very advanced system of hardware, systems meant for facial identification ave evolved enormously over the past few decades. Sketch recognition is one of the most important areas that have evolved as an integral component adopted by the agencies of law administration in current trends of forensic science. Matching of derived sketches to photo images of face is also a difficult assignment as the considered sketches are produced upon the verbal explanation depicted by the eye witness of the crime scene and may have scarcity of sensitive elements that exist in the photograph as one can accurately depict due to the natural human error. Substantial amount of the novel research work carried out in this area up late used recognition system through traditional extraction and classification models. But very recently, few researches work focused on using deep learning techniques to take an advantage of learning models for the feature extraction and classification to rule out potential domain challenges. The first part of this review paper basically focuses on deep learning techniques used in face recognition and matching which as improved the accuracy of face recognition technique with training of huge sets of data. This paper also includes a survey on different techniques used to match composite sketches to human images which includes component-based representation approach, automatic composite sketch recognition technique etc.
9 citations
09 Sep 2010
TL;DR: To improve the efficiency of drawing the graphic symbols of the scene of traffic accident, a SS-based sketch recognition technology is introduced into the identification of traffic sketches and practical application proves the proposed method both effective and efficient.
Abstract: To improve the efficiency of drawing the graphic symbols of the scene of traffic accident, a SS-based sketch recognition technology is introduced into the identification of traffic sketches. While four basic cartography factors, including straight line, polyline, circle and arc, are put forward to partition the intricate sketch into the combination of multi-strokes, according to the basic characteristic of the graphics. Online sketch recognition can reveal latent primitive shapes and show the regularized shape on screen immediately through feature recognition, shape fitting and regularization. After the primitive stroke are grouped according to the spatial relationships, the user's intention is caught and suggested through computing their similarity with the predefined templates both in partial structures as well as in overall configuration. Practical application proves the proposed method both effective and efficient.
9 citations
TL;DR: The result of the application of proposed novel methods of automatic sketch generation on two popular face database are given and it is shown that for sketch recognition you can use simple system.
Abstract: Article presents the state of the art problem of comparing photo portrait and the corresponding hand-drawn portrait (sketch). Proposed novel methods of automatic sketch generation. The result of the application of this methods on two popular face database are given. It is shown that for sketch recognition you can use simple system.
9 citations
18 May 2015
TL;DR: This work proposes a method using joint dictionary learning for face photo-sketch recognition that bypasses the image synthesis procedure used by previous joint Dictionary learning based methods and achieves recognition rates higher than or comparable to that of the state-of-art methods.
Abstract: Face recognition technology is widely used in law enforcement agencies. Face photo-sketch recognition is one of possible ways to identify suspects. We propose a method using joint dictionary learning for face photo-sketch recognition. Our method bypasses the image synthesis procedure used by previous joint dictionary learning based methods. Compared with other methods such as coupled dictionary learning which projects features from two different modalities into a common space for recognition, our method does not need extra projections, and avoids the expensive optimization of coupled dictionary learning. By using the cosine distance nearest neighbor classifier, our method performs equally well as coupled dictionary learning based method with much less computation. In the experiments on a popular face photo-sketch database, our method achieves recognition rates higher than or comparable to that of the state-of-art methods.
9 citations
01 Jan 2016
TL;DR: SmartStrokes, a testing suite that implements digital versions of common clinical neuropsychology pencil-and-paper tests, is developed with the purpose of helping to automate and analyze patient sketches using the principles of sketch recognition.
Abstract: Clinical neuropsychologists develop comprehensive behavioral profiles on their patients primarily by using paper-and-pencil test stimuli. Despite these tests being significantly cheaper and faster than complex procedures such as MRI scans, multiple drawbacks remain. Constructing these behavioral profiles can take upwards of six hours to fully complete, and the analysis of the sketches from these pencil-and-paper tests is still largely subjective and qualitative. We developed SmartStrokes, a testing suite that implements digital versions of common clinical neuropsychology pencil-and-paper tests, with the purpose of helping to automate and analyze patient sketches using the principles of sketch recognition.
9 citations