Semantic human activity recognition: A literature review
We have conducted a detailed review on recent action recognition frameworks based on semantic information for the first time. A semantic space is introduced that mainly includes pose, poselet, object/scene context, and attributes. We discuss that semantic descriptions capture meaningful information and are robust to visual variations. We show that semantic methods outperform non-semantic methods in most cases with comparing their performances. We present some directions to motivate future researchers to devote more attention to semantic information.
human activity recognition pose poselet scene attribute human-object interaction survey