Titlebook: Representations, Analysis and Recognition of Shape and Motion from Imaging Data; 7th International Wo Liming Chen,Boulbaba‘Ben Amor,Faouzi

抓住他投降

推崇

A Normalized Generalized Curvature Scale Space for 2D Contour Representation descriptor. It consists on the convolution of the contour by Gaussian functions with different scales. The points having the same curvature values as the selected extremums are the considered key points. This representation implies different number of descriptors from a shape to another. Thus, a st

ostrish

A New Watermarking Method Based on Analytical Clifford Fourier Mellin Transform order to process colored images. The proposed Fourier Transform is called Clifford Analytical Fourier Mellin Transform (CAFMT). Its magnitude, same as AFMT modulus, is invariant against planar similarities, not only on gray level images but also on colored images. Using ACFMT magnitude, we propose

CIS

Simultaneous Semi-supervised Segmentation of Category-Independent Objects from a Collection of Imageropagate the segmentation information between images in order to detect foreground objects in all these images simultaneously, under the hypothesis of using categorized or uncategorized images, rather than resorting to image co-segmentation that forces the use of similar categorized images. In fact,

concert

Conference proceedings 2019 Imaging Data, RFMI 2017, held in Savoi, France, in December 2017..The 8 revised full papers and 9 revised short papers presented were carefully reviewed and selected from 23 submissions. The papers are organized in topical sections on analyzing motion data; deep learning on image and shape data; 2D

Ointment

Multi-person Head Segmentation in Low Resolution Crowd Scenes Using Convolutional Encoder-Decoder Frnd faces in an image patch are simultaneously detected contrasting to the traditional sliding window based detectors. Compared to the existing state-of-the-art methods, the proposed algorithm has demonstrated excellent performance on a challenging spectator crowd dataset.

CERE

Thymus

Simultaneous Semi-supervised Segmentation of Category-Independent Objects from a Collection of Imageestimated to optimize the proposed energy function. Then, an iterative optimization of each image permits to remarkably optimize the final segmentation result for all images composing the input collection. Extensive experiments demonstrate that the suggested method allows full-object segmentation of

ALE

Ronny Hug,Stefan Becker,Wolfgang Hübner,Michael Arens

卧虎藏龙

Ichraf Lahouli,Robby Haelterman,Zied Chtourou,Geert De Cubber,Rabah Attia