Multi-modal Person Identification

SEDMIDUBSKÝ, Jan, Jakub VALČÍK and Pavel ZEZULA. Multi-modal Person Identification. 2015.

Basic information

• Original name: Multi-modal Person Identification
• Authors: SEDMIDUBSKÝ, Jan (203 Czech Republic, guarantor, belonging to the institution), Jakub VALČÍK (203 Czech Republic, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution).
• Edition: 2015.

Other information

• Original language: English
• Type of outcome: Software
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: Czech Republic
• Confidentiality degree: is not subject to a state or trade secret
• WWW: URL
• RIV identification code: RIV/00216224:14330/15:00080528
• Organization unit: Faculty of Informatics
• Keywords in English: multi-modal person identification; face recognition; walk cycle recognition; motion retrieval
• Technical parameters: The more detailed information about this technology along with the information about software acquisition is available at: http://disa.fi.muni.cz/prototype-applications/person-identification/. Odpovědná osoba pro jednání: prof. Ing. Pavel Zezula, CSc., Fakulta informatiky, Masarykova univerzita, Botanická 68a, Brno, tel.: [phone]
• Tags: DISA
• Tags: International impact

Abstract

Multi-modal Person Identification (MMPI) is a software technology for multi-modal recognition of persons according to their faces and the way they walk. The recognition process is based on analysis of detected face images and motion capture data — both acquired by motion capturing devices, including popular Microsoft Kinect and ASUS Xtion. The acquired data are firstly preprocessed by (1) detecting face images and extracting MPEG-7 face features and (2) detecting walk cycles and extracting movement features in form of relative velocities of the specific joints for each walk cycle. Both the face and walk-cycle features extracted from a query motion are used to retrieve two independent sets of the most similar faces and walk cycles. These retrieved sets are processed by a multi-modal classification method to recognize the query person identity. The MMPI technology is demonstrated via a web application that allows users to select a query motion and verify whether the technology recognizes the query person correctly.

Links

• VG20122015073, research and development project: Name: Efektivní vyhledávání v rozsáhlých biometrických datech (Acronym: EFBIO)

Investor: Ministry of the Interior of the CR