Temporal Action Detection Based on Action Temporal Semantic Continuity | Zendy

Yanchun Wu | Zendy; Jianqin Yin | Zendy; Lei Wang | Zendy; Huaping Liu | Zendy; Qi Dang | Zendy; Zhiming Li | Zendy; Yilong Yin | Zendy

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Temporal Action Detection Based on Action Temporal Semantic Continuity

Author(s) -

Yanchun Wu,

Jianqin Yin,

Lei Wang,

Huaping Liu,

Qi Dang,

Zhiming Li,

Yilong Yin

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2842428

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

This research proposes a method for optimizing extracted candidate proposals based on the action temporal semantic continuity rule to accurately detect the category and start and end time in the temporal action detection of long untrimmed videos. First, sliding windows of the same scale and different scales are integrated according to the rule of action temporal semantic continuity. Subsequently, we reacquire the classification confidence score and relocate the integration results. Finally, inaccurate detections are eliminated by non-maximum value suppression. In contrast to the specified scale of the detection results obtained by sliding window, this method can produce the action temporal segments of any length and suppress the redundant detection. Therefore, the detection results are more consistent with the expectation of an individual. Experimental results show that the mean average precision increases from 19.0% to 20.6% when the intersection-over-union threshold is set to 0.5 on THUMOS 2014 data set.

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