A Survey of Sound-based Biometrics used in Species Recognition

被引:0
|
作者
Wei, Yuqiu [1 ]
Xu, Yiling [1 ]
Latifi, Shahram [1 ]
机构
[1] Univ Nevada, Las Vegas, NV 89154 USA
关键词
Behavioral Biometric; Feature Extraction; Frequency Cepstrum Coefficient; Mel Filter; Species Recognition;
D O I
10.1109/iemcon.2019.8936277
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Preserving animals and, in particular, endangered animals is of paramount importance which is pointed out by environmentalists, biologists and other life scientists frequently. In tracking and monitoring such animals, people often use visual clues such as shape, color and physical attributes to search for species of interest. Such clues while useful, may prove ineffective at times due to weather condition, pollution and other natural phenomena that may impair the acquisition of a clear image/video. This paper focuses on developing audio signatures based on sounds made by animals of interest and utilizing these signatures to locate and track such animals. The problem addressed here may be viewed as a behavioral biometrics problem as the goal here is to automate classification/identification of species based on their audio signatures. Here, the theoretical basis for developing a species recognition system using the sound produced by such species is addressed. Acquisition of sound data, preprocessing, filtering and finally classification of such data are described in detail.
引用
收藏
页码:197 / 201
页数:5
相关论文
共 50 条
  • [41] Sound-based approach to video indexing and its application
    Minami, K.
    Akutsu, A.
    Hamada, H.
    Tonomura, Y.
    Systems and Computers in Japan, 1998, 29 (12): : 1 - 10
  • [42] Sound-Based Anomalies Detection in Agricultural Robotics Application
    Baltazar, Andre Rodrigues
    dos Santos, Filipe Neves
    Soares, Salviano Pinto
    Moreira, Antonio Paulo
    Cunha, Jose Boaventura
    PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2023, PT II, 2023, 14116 : 338 - 350
  • [43] Ambient Sound-Based Collaborative Localization of Indeterministic Devices
    Kamminga, Jacob
    Duc Le
    Havinga, Paul
    SENSORS, 2016, 16 (09)
  • [44] Sound-based Thinking and Design Practices with Embodied Extensions
    Lewis, Erin
    Stasiulyte, Vidmina
    TEI'20: PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE ON TANGIBLE, EMBEDDED, AND EMBODIED INTERACTION, 2020, : 889 - 892
  • [45] Attempt to develop a sound-based examination monitoring system
    Ueda, Mari
    Tanaka, Tetsuo
    Hasegawa, Hideyuki
    ACOUSTICAL SCIENCE AND TECHNOLOGY, 2021, 42 (04) : 226 - 227
  • [46] Author Correction: Flow prediction in sound-based uroflowmetry
    Marcos Lazaro Alvarez
    Laura Arjona
    Mario Jojoa-Acosta
    Alfonso Bahillo
    Scientific Reports, 15 (1)
  • [47] Sound-Based Construction Activity Monitoring with Deep Learning
    Xiong, Wuyue
    Xu, Xuenan
    Chen, Long
    Yang, Jian
    BUILDINGS, 2022, 12 (11)
  • [48] A constructivist approach for opening minds to sound-based music
    Holland, David
    JOURNAL OF MUSIC TECHNOLOGY & EDUCATION, 2015, 8 (01) : 23 - 39
  • [49] Validation of an algorithm for sound-based voided volume estimation
    Jung, Gyoohwan
    Ryu, Hoyoung
    Lee, Jeong Woo
    Jeong, Seong Jin
    Margolis, Eric
    Grover, Neel
    Lee, Sangchul
    SCIENTIFIC REPORTS, 2024, 14 (01)
  • [50] Reduction of spatial sampling requirement in sound-based synthesis
    Nguyen, Cac
    Morrison, Robert L., Jr.
    Do, Minh N.
    2007 2ND IEEE INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING, 2007, : 173 - 176