Ms. Lili Jia Profile

Lili Jia

at Shanghai Key Lab of Field Evidence

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Proceedings Article | 31 January 2020 Paper

Clothing mark index system with image saliency in surveillance videos

Lili Jia, Wenbin Liu, Wei Chen

Proceedings Volume 11427, 114273Q (2020) https://doi.org/10.1117/12.2553063

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In order to strengthen the management and control of special crowd and increase the application effectiveness of video as a typical unstructured data, this paper focuses on how to effectively extract and utilize the rich content contained in it to transform into intelligence information and build an effective personnel-specific tracking system. The experimental results show that the combination of video motion region extraction and personnel image features can more accurately complete person detection, and the introduction of multi-feature fusion to extract special person regions, such as clothing logo identification and other areas, for specific person to carry out feature labeling to index, improve the accuracy of personnel tracking. From the perspective of police technology innovation, this paper introduces the method of personnel characteristics analysis, comparison, retrieval, data mining and intelligent early warning to improve the application level of valuable personnel characteristics data in video images, and establish a feature analysis system to achieve continuous tracking of targets.

Proceedings Article | 31 August 2018 Paper

Automatic human hallmark recognition based on visual words

Lili Jia, Wei Chen, Wenbin Liu

Proceedings Volume 10835, 108350B (2018) https://doi.org/10.1117/12.2505629

KEYWORDS: Visualization, Image retrieval, Image processing, Feature extraction, Associative arrays, Databases, Quantization, Image classification, Biometrics, Image storage

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Human hallmarks, as an important biometric traits, contain discriminative characteristics information to support person identification due to its saliency in visual attention. A sketch of a tattoo can be drawn based on the description provided by an eyewitness or the victim. In this paper, the authors propose a novel hallmark photo-sketch recognition method using a bag-of-words (BoW) methodology for retrieving the photos in the database based on a query sketch or image drawn by an artist. And this article discusses the number of visual words generated which is based on the number of clusters, including vocabulary size, weighting scheme. Extensive experiments are conducted on a sketch database including 100 tattoo sketches drawn by three different subjects. Each sketch has a corresponding tattoo image, which is downloaded from the internet. It is an effective and viable application to develop operationally-relevant automated image-based tattoo recognition applications for pertinent law enforcement operational scenarios.

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