Static Shot based Keyframe Extraction for Multimedia Event Detection

2. Related Works

Many researchers focus on the keyframe extraction which can be used for various applications like video summarization, video retrieval, and video event detection and so on. As keyframe extraction has become a basic step for various domains based applications, it can be extracted and can be used efficiently for detection of events in the video sequences. Keyframes can be extracted using low level and high level features. Low level features includes color, edge, texture, motion features etc. Whereas high level features include semantic information. Various high level features are discussed in the paper (Chen et al., 2011), in which, according to the camera movement selection and automatic scene analysis, keyframes are extracted from the specific domain (basketball) videos. In the paper (Mezaris et al., 2013), high level features are traced using low level interest point detection and description which is suitable to generate Bag of Spatiotemporal Words (BOSW). Whereas, in the paper (Younessian et al., 2012), the author addresses the semantic relatedness based on textual, auditory and visual clues. The major disadvantage of using high level features is, it is not applicable for all domains due its complexity in nature.