메뉴 건너뛰기




Volumn , Issue , 2016, Pages 102-106

Action recognition based on joint trajectory maps using Convolutional Neural Networks

Author keywords

Action recognition; Convolutional Neural Networks; Skeleton; Trajectory

Indexed keywords

COMPUTER VISION; CONVOLUTION; GESTURE RECOGNITION; IMAGE RECOGNITION; MOTION ESTIMATION; MUSCULOSKELETAL SYSTEM; NEURAL NETWORKS; TRAJECTORIES;

EID: 84994571080     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2964284.2967191     Document Type: Conference Paper
Times cited : (305)

References (28)
  • 2
    • 84956626439 scopus 로고    scopus 로고
    • Utd-mhad: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor
    • C. Chen, R. Jafari, and N. Kehtarnavaz. Utd-mhad: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor. In Image Processing (ICIP), 2015 IEEE International Conference on, pages 168-172, 2015.
    • (2015) Image Processing (ICIP), 2015 IEEE International Conference on , pp. 168-172
    • Chen, C.1    Jafari, R.2    Kehtarnavaz, N.3
  • 11
    • 84951985479 scopus 로고    scopus 로고
    • A generative restricted boltzmann machine based method for high-dimensional motion data modeling
    • S. Nie, Z. Wang, and Q. Ji. A generative restricted boltzmann machine based method for high-dimensional motion data modeling. Computer Vision and Image Understanding, pages 14-22, 2015.
    • (2015) Computer Vision and Image Understanding , pp. 14-22
    • Nie, S.1    Wang, Z.2    Ji, Q.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.