Global motion estimation based video saliency detection method

Abstract

The invention relates to a global motion estimation based video saliency detection method. The method is characterized by comprising the following steps of extracting a spatial domain characteristic and a time domain characteristic in a compressed code-stream, and obtaining a spatial domain saliency image by using a two-dimensional Gaussian weighting function and the spatial domain characteristic; filtering a background motion vector belonging to global motion by using a cascaded structure, obtaining a rough time domain saliency image on the basis of residual motion vectors, and optimizing the rough time domain saliency image according to macroblock information; and according to a human visual characteristic and characteristics of the time domain saliency image and the spatial domain saliency image, performing self-adaptive fusion on the time domain saliency image and the spatial domain saliency image so as to obtain an image salient area. The global motion estimation based video saliency detection method is reasonable in design, and considers complete characteristic types in detection of spatial domain saliency and time domain saliency, so that the final saliency image further conforms to subjective perceptual quality of human eyes, has high robustness, does not change in dependence of video content, has strong expandability, and also can use the fusion manner of the invention if being added with other characteristics.

Description

technical field [0001] The invention belongs to the technical field of video detection, and in particular relates to a video saliency detection method based on global motion estimation. Background technique [0002] With the vigorous development of Internet technology and communication technology, people acquire and exchange more and more information in their daily life. The information includes text, images, audio and video, etc. Since video contains a large amount of information and rich content, video has become the main information carrier. However, such a huge amount of information will be limited by bandwidth and capacity when it is transmitted and stored, so it needs to be processed according to the visual characteristics of the information receptor human eyes to extract the parts that the human eyes pay attention to. Video saliency detection is an important mechanism for analyzing video information according to the visual characteristics of the human eye. It can be ...

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Problems solved by technology

Muthuswamy et al. (Karthik Muthuswamy and Deepu Rajan, "Salient motion detection in compressed domain," IEEE Signal Processing Letters, vol.20, pp.996–999, 2013.) proposed a two-layer structure algorithm for distinguishing salient motion, However, it does not solve the fusion problem of saliency maps under various feature conditions.

Fang (Yuming Fang, Zhou Wang, and Weisi Lin, "Video saliency incorporating spatiotemporal cues and uncertainty weighting," in Multimedia and Expo (ICME), 2013IEEE International Conference on. IEEE, 2013, pp.1–6.) etc. proposed based on The adaptive fusion method of the local uncertainty measure can achieve better detection results, but this method needs to know the real saliency map in advance when calculating the weight, which hinders the practical application of this method, and this method is not suitable for video Scenes with global motion in

[0006] To sum up, among the existing video saliency detection methods, there are few compressed domain methods, which do not consider the impact of global motion on the detection results, and the saliency map fusion technology under multiple features is not perfect enough to give full play to each feature. Advantages of testing results under conditions

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