Homography Estimation Method Research Articles

Robust Painting Recognition and Registration for Mobile Augmented Reality

In this work we introduce a novel approach for painting recognition and registration for mobile Augmented Reality applications. To address the challenges of real-time painting recognition and registration we introduce three main contributions: i) A relevant painting region detector extracts the painting region from the given image. ii) Two local and global features are extracted from the relevant region to robustly match a painting database. iii) A RANSAC homography estimation method is used to overlay the additional content in an AR framework. Experiments have been carried out on a dataset built with publicly available images.

효율적인 호모그래피 추정을 통한 파노라마 영상 생성

본 논문에서는 고해상도 영상에서 호모그래피를 효율적으로 추정하는 방법을 제안하였다. 호모그래피를 정확하게 추정하는 것은 영상 정합 기술에서 가장 중요한 부분이다. 하드웨어의 급속한 발전으로 고해상도 영상을 쉽게 취득 할 수 있게 되었지만, 데이터의 크기가 증가함에 따라 정확한 일치관계를 추정하는데 많은 계산량이 요구되었다. 또한, 고해상도의 영상에서 확률적으로 부정확한 호모그래피가 추정되는 문제가 발생하였다. 따라서 우리는 원 영상을 각 스케일별로 다운 샘플링한 다수의 영상을 생성하여 각 다운 샘플링된 영상에 해당하는 호모그래피를 추정한 후 투영 오차가 가장 작은 것을 선택하여 원 영상에 적용할 수 있게 보정할 수 있는 방법을 제안하였다. 또한, 영상을 정합하는 과정에서 기준 영상과 대상 영상의 색상 톤의 차이가 큰 경우에는 중첩영역의 지역 정보만을 이용하여 기준 영상과 대상 영상의 색상 톤을 일치시키는 방법을 제안하였다. 실험 결과 기존의 방법보다 3.2M 픽셀의 해상도 영상에서 약 3배, 8M 픽셀의 해상도 영상에서 약 5배 이상 빠른 결과를 얻을 수 있음을 확인하였다. 이는 입력 영상의 해상도가 커질수록 제안한 방법의 효과가 더 커진다는 것을 보여준다.

HEASK: Robust homography estimation based on appearance similarity and keypoint correspondences

Accurate homography estimation is a classical problem with high industrial value and has been investigated extensively. Most previous homography estimation methods used either appearance similarity or keypoint correspondences to find their best estimation. In this paper, a novel algorithm is proposed which integrates the advantages of the pixel-based and the feature-based homography estimation approaches. We elegantly combined the probability models of appearance similarity and keypoint correspondences in a Maximum Likelihood framework, which is named as Homography Estimation based on Appearance Similarity and Keypoint correspondences (HEASK). In the model of keypoint correspondences, the distribution of inlier location error is represented by a Laplacian distribution, which outperforms the previous Gaussian distribution in characterizing heavy-tailed distributions. And in the model of appearance similarity, the enhanced correlation coefficient (ECC) is adopted for describing image similarity, and the distribution of ECC is studied and parametrically formulated using a truncated exponential distribution. The proposed model is solved based on an improved framework of random sample consensus (RANSAC). Several simulations summarize the performance of the proposed approach in objective quality measurement, subjective visual quality, and computation time. The experimental results demonstrate that the proposed approach can achieve more accurate homography estimation under different image transformation degrees and with different ratios of inlier keypoint correspondences as compared to the state-of-the-art works.

Watermarking of Free-view Video

With the advances in image based rendering (IBR) in recent years, generation of a realistic arbitrary view of a scene from a number of original views has become cheaper and faster. One of the main applications of this progress has emerged as free-view TV(FTV), where TV-viewers select freely the viewing position and angle via IBR on the transmitted multiview video. Noting that the TV-viewer might record a personal video for this arbitrarily selected view and misuse this content, it is apparent that copyright and copy protection problems also exist and should be solved for FTV. In this paper, we focus on this newly emerged problem by proposing a watermarking method for free-view video. The watermark is embedded into every frame of multiple views by exploiting the spatial masking properties of the human visual system. Assuming that the position and rotation of the virtual camera is known, the proposed method extracts the watermark successfully from an arbitrarily generated virtual image. In order to extend the method for the case of an unknown virtual camera position and rotation, the transformations on the watermark pattern due to image based rendering operations are analyzed. Based upon this analysis, camera position and homography estimation methods are proposed for the virtual camera. The encouraging simulation results promise not only a novel method, but also a new direction for watermarking research.