Research Article
Representation for Action Recognition Using Trajectory-Based Low-Level Local Feature and Mid-Level Motion Feature
Table 2
Accuracy comparisons of different methods on KTH, YouTube and J-HMDB datasets.
| KTH | YouTube | J-HMDB |
| ISA [15] | 86.5% | Liu et al. [16] | 71.2% | Traditional FV [17] | 62.83% | Yeffet and Wolf [18] | 90.1% | Ikizler-Cinbis and Sclaroff [19] | 75.21% | Stacked FV [17] | 59.27% | Cheng et al. [20] | 89.7% | DT + BoVW [1] | 85.4% | DT + BOW [10] | 56.6% | Le et al. [15] | 93.9% | Mid-level parts [21] | 84.5% | IDT + FV [17] | 62.8% |
| Two-layer model | 92.6% | Two-layer model | 87.6% | Two-layer model | 67.4% |
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