Motion Fused Frames: Data Level Fusion Strategy for Hand Gesture Recognition

Acquiring spatio-temporal states of an action is the most crucial step for action classification. In this paper, we propose a data level fusion strategy, Motion Fused Frames (MFFs), designed to fuse motion information into static images as better representatives of spatio-temporal states of an action... (read more)

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Datasets


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Hand Gesture Recognition ChaLean test 8-MFFs-3f1c Accuracy 56.7 # 1
Hand Gesture Recognition ChaLearn val 8-MFFs-3f1c (5 crop) Accuracy 57.4 # 1
Hand Gesture Recognition Jester test DRX3D Top 1 Accuracy 96.6 # 1
Hand Gesture Recognition Jester val 8-MFFs-3f1c (5 crop) Top 1 Accuracy 96.33 # 1
Top 5 Accuracy 99.86 # 1
Hand Gesture Recognition NVGesture 8-MFFs-3f1c Accuracy 84.7 # 3

Methods used in the Paper


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