No abstract

Obtaining an accurate vehicle position is important for intelligent vehicles in supporting driver safety and comfort. This paper proposes an accurate ego-localization method by matching in-vehicle camera images to an aerial image. There are two major problems in performing an accurate matching: (1) image difference between the aerial image and the in-vehicle camera image due to view-point and illumination conditions, and (2) occlusions in the in-vehicle camera image. To solve the first problem, we use the SURF image descriptor, which achieves robust feature-point matching for the various image differences. Additionally, we extract appropriate feature-points from each road-marking region on the road plane in both images. For the second problem, we utilize sequential multiple in-vehicle camera frames in the matching. The experimental results demonstrate that the proposed method improves both ego-localization accuracy and stability.

No abstract

No abstract

No abstract

No abstract

Abstract-The

A 74-year-old woman had an undifferentiated carcinoma with osteoclast-like giant cells (UCWOGC) in the body of the pancreas with massive portal vein tumor thrombus (PVTT). Because the PVTT progressed so rapidly into the right portal branch, the patient first underwent distal pancreatectomy and tumor thrombectomy to prevent life-threatening portal venous obstruction. Although a recurrent PVTT had developed early postoperatively, systemic gemcitabine treatment was so effective that it induced complete remission 5 months after the initiation of chemotherapy. The patient continued to be in complete response for 12 months, and has survived for 19 months since surgery.