The present invention discloses a multi-thread significance method based on a light field camera. The method comprises: 1, employing a Lytro light field camera to collect five-dimensional light field data in a scene and obtains light field full-focusing images, depth images, a focus stack image sequence and a multi-view image sequence; 2, performing super-pixel segmentation of the full-focusing images, and extracting the color, the position and the depth difference characteristics between the pixel pairs on different light field images; 3, respectively extracting the average optical flow characteristics of an adjacent focal plane image and an adjacent visual angle image, and calculating the focus flow difference characteristics and the visual angle flow difference characteristics; 4, performing weighting and summation of the color, the depth, the focus flow and the visual angle flow difference characteristics, and taking the position difference characteristic as a weight, and obtaining the original substantial results of multiple clues; and 5, optimizing the original substantial results, and obtaining the multiple-clue significance of the light field camera. The multi-thread significance method based on a light field camera is able to solve the defect that the current two-dimensional and three-dimensional significance extraction method cannot obtain and use the vision multiple clues so as to effectively improve the extraction precision of the image significance in the complex changeable scene.