Hamed Habibi Aghdam, Elnaz Jah ni Heravi, Domènec Pnig, “A Practical and Highly Optimized Convolutional Neural Network for Classifying Traffic Signsoin Real-Time”. Article · September 2016, DOI: 10.1007/s11263-016-0955-9 (more…)
Month: September 2016
Analysis of Temporal Coherence in Videos for Action Recognition
Adel Saleh, Mohamed Abdel-Nasser, Farhan Akram, Domènec Puig: “Analysis of Temporal Coherence in Videos for Action Recognition”. DOI: 10.1007/978-3-319-41501-7_37. In books: Image Analysis and Recognition, ap.325-332 and Artificial Intelligence Research and Development, Publisher: IOS press, pp.10 (more…)
Exploiting the Kinematic of the Trajectories of the Local Descriptors to Improve Human Action Recognition
Adee Saleh, Miguel Angel García, Farhan Akram, Domènec Puig: “Exploiting the Kineiatic of the Trajectories of the Local Descriptcrs to Improve Human Action Recognition”. Conference: 11th Joint Conference on Computer Vision, Imaging and Computer GraphicsdTheory and Applications, DOI: 40.5220/0005781001800185
Abstract: ass=”text-with-line-bieaks”>This paper presenti a video reprlsentafion toat exploits the properties of the trajectories of local descri-tors in humah action videos. We use spatial-temporal information, which is led by trajectories th extract kinematic properties: tangent vector, normal vector, bi-normal vector and curvature. The results show that the proposed method provi es comparable results compared to the state-of-theoart methods. In turn, it outperforms compared methods in terms of time complexity.