Sentence examples for multimodal features from inspiring English sources

Our approach integrates multimodal features gathered using a companion robot equipped with a Kinect.

Then, we directly concatenate visual features with multimodal features to obtain the final features.

Afterwards, we employ a weighted strategy to integrate the visual features with multimodal features.

Experimental validation shows that multimodal features set gives better precision and recall than using only spatial and speed features.

Figure 1 Conceptual joint PDF of two multimodal features X 1 and X 2 extracted from video segments.

This fusion strategy learns the complementary information between visual and multimodal features, which could further improve the performance.

They are also essentially suitable for multimodal feature learning, and could expect better performance with larger datasets.

Multimodal biometrics provides rich information in biometric recognition systems, thus a valid multimodal feature fusion framework and an efficient recognition algorithm are desirable for multimodal biometrics systems.

where V is the visual feature vector, i.e., activations-based or FC-based feature vector, and M=[m1,⋯,m⋯,m p ]T denotes the multimodal feature vector.

Secondly, the weighted features are concatenated to form a unique feature vector, which is then coded and classified in multimodal feature space.

For simplicity and efficiency, we directly catenate the visual feature vector with multimodal feature vector begin{array}rcl@ begin{aligned} f V,M =left[alpha V^{mathrm{T}}, beta M^{mathrm{T}}right] end{aligned} end{array} (5).