By Deepak Ghimire, Joonwhoan Lee (auth.), Yo-Sung Ho (eds.)
The two-volume lawsuits LNCS 7087 + LNCS 7088 represent the lawsuits of the fifth Pacific Rim Symposium on photograph and Video expertise, PSIVT 2011, held in Gwangju, Korea, in November 2011. the entire of seventy one revised papers used to be rigorously reviewed and chosen from 168 submissions. the themes coated are: image/video coding and transmission; image/video processing and research; imaging and snap shots and visualization; image/video retrieval and scene figuring out; biomedical picture processing and research; biometrics and photograph forensics; and desktop imaginative and prescient applications.
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Extra resources for Advances in Image and Video Technology: 5th Pacific Rim Symposium, PSIVT 2011, Gwangju, South Korea, November 20-23, 2011, Proceedings, Part I
Furthermore, in order to examine the visual fatigue of the stereoscopic image viewing, we performed subjective visual Fig. 11. Subjective grades with respect to (a) τ and (b) σ S Fig. 12. Subjective test for visual fatigue with respect to τ 3D Perception Adjustment of Stereoscopic Images Based upon Depth Map 21 fatigue test. Visual fatigue was subjectively judged on a scale of 1 (severe fatigue), 2 (fatigue), 3 (mild fatigue), 4 (slight fatigue) and 5 (not at all). As validated in Fig. 0, which means that the proposed method makes comfortable stereoscopic images.
Five depth planes are shown in Fig. 5. Fig. 5. Five depth planes of Breakdance Table 1. Standard deviation of input and output depth planes. (* denotes the range-changed depth planes). 8, at the first iteration, we can not achieve σ T . 1. Then in the second iteration, the condition was met at the depth plane 4. A final σ S is 786. 7, the second iteration was completed with depth plane 3. A final σ S is 685. 1. The final depth planes are shown in Fig. 6. (a) (b) Fig. 6. 7 3D Perception Adjustment of Stereoscopic Images Based upon Depth Map 19 Fig.
3. 1 Semi-global Stereo Matching The purpose of stereo matching, given two or more input images, is to ﬁnd pixel correspondences between the images. This is equivalent to depth estimation if the camera parameters are known. Typically, one of the input images is selected as the basis image for which the depth value of each pixel is estimated. , depth values should not vary drastically except around the object boundaries). These conditions are represented as an energy minimization problem, whose optimal solution can be found using sophisticated numerical methods.
Advances in Image and Video Technology: 5th Pacific Rim Symposium, PSIVT 2011, Gwangju, South Korea, November 20-23, 2011, Proceedings, Part I by Deepak Ghimire, Joonwhoan Lee (auth.), Yo-Sung Ho (eds.)