3D Gestural Interaction: The State of the Field

Table 1

A table summarizing different 3D gesture recognition approaches, the size of the gesture set, and the stated recognition accuracy.

Author	Recognition approach	Number of gestures	Accuracy
Pang and Ding [58]	HMMs with kinematic features	12	91.2%
Wan et al. [60]	HMMs with sparse coding	4	94.2%
Lee and Cho [61]	Hierarchical HMMs	3	Approx. 80.0%
Whitehead and Fox [68]	Standard HMMs	7	91.4%
Nguyen et al. [66]	Two-stage HMMs	10	95.3%
Chen et al. [63]	HMMs with Fourier descriptors	20	93.5%
Pylvänäinen [67]	HMMs without rotation data	10	99.76%
Chung and Yang [71]	Threshold CRF	12	91.9%
Yang et al. [72]	Two-layer CRF	48	93.5%
Yang and Lee [73]	HCRF with BoostMap embedding	24	87.3%
Song et al. [78]	HCRF with temporal smoothing	10	93.7%
Liu and Jia [80]	HCRF with manifold learning	10	97.8%
Elmezain and Al-Hamadi [83]	LDCRF with depth camera	36	96.1%
Song et al. [84]	LDCRF with filtering framework	24	75.4%
Zhang et al. [85]	Fuzzy LDCRF	5	91.8%
Huang et al. [88]	SVM with Gabor filters	11	95.2%
Hsieh et al. [89]	SVM with Fourier descriptors	5	93.4%
Hsieh and Liou [90]	SVM with Haar features	4	95.6%
Dardas and Georganas [92]	SVM with bag of words	10	96.2%
Chen and Tseng [93]	Fusing multiple SVMs	3	93.3%
Rashid et al. [94]	Combining SVM with HMM	18	98.0%
Yun and Peng [101]	Hu moments with SVM	3	96.2%
Ren and Zhang [99]	SVM with min enclosing ball	10	92.9%
Wu et al. [100]	Frame-based descriptor with SVM	12	95.2%
He et al. [96]	SVM with Wavelet and FFT	17	87.4%
Nisar et al. [104]	Decision trees	26	95.0%
Jeon et al. [105]	Multivariate fuzzy decision trees	10	90.6%
Zhang et al. [106]	Decision trees fused with HMMs	72	96.3%
Fang et al. [107]	Hierarchical Decision trees	14	91.6%
Miranda et al. [109]	Decision forest with key pose learning	10	91.5%
Keskin et al. [41]	Decision forest with SVM	10	99.9%
Keskin et al. [110]	Shape classification forest	24	97.8%
Negin et al. [111]	Feature selection with decision forest	10	98.0%
Ellis et al. [74]	Logistic regression	16	95.9%
Hoffman et al. [112]	Linear classifier	25	99.0%
Kratz and Rohs [113]	$3 gesture recognizer	10	80.0%
Kratz and Rohs [114]	Protractor 3D (rotation invariance)	11	Approx. 91.0%