Graphs are frequently used to provide a powerful representation for structured data. However, it is still a challenging task to model 3D human motions due to its large spatio-temporal variations. This paper proposes a novel graph-based method for real time 3D human motion retrieval. Firstly, we propose a novel graph construction method which connects the joints that are deemed important for a g...

Assessing the structure and function of right ventricle (RV) is important in diagnosis several cardiac pathologies. However, it remains more challenging to segment RV than left (LV). In this paper, we focus on segmenting both short (SA) long-axis (LA) MR images simultaneously. For task, propose a new multi-input/output architecture, hybrid 2D/3D geometric spatial TransformEr Multi-Pass fEature ...

-The stochastic pyramid is introduced in landscape ecology in order to propose a spatial organization model of ecological units in river floodplains. It consists in articulating this parallel generator of random patterns with ecological processes. The stochastic pyramid, based on a hierarchy of seed structures, is used to make regions grow in order to obtain random patterns relating to an a pri...

In order to support content-based iconic image retrieval efficiently, we propose a new spatial-match representation scheme, called SR scheme, which combines directional operators with positional operators. Therefore, our scheme can represent spatial relationships between icon objects precisely and can provide ranking for the retrieved images. In addition, we compare our scheme with the conventi...

We generalize image-based rendering by exploiting texture-mapping graphics hardware to decompress ray-traced “animations”. Rather than 1D time, our animations are parameterized by two or more arbitrary variables representing view/lighting changes and rigid object motions. To best match the graphics hardware rendering to the input ray-traced imagery, we describe a novel method to infer parameter...

Matching of keypoints across image patches forms the basis of computer vision applications, such as object detection, recognition, and tracking in real-world images. Most of keypoint methods are mainly used to match the high-resolution images, which always utilize an image pyramid for multiscale keypoint detection. In this paper, we propose a novel keypoint method to improve the matching perfor...

This paper presents an effective scene classification approach based on collaborative representation fusion of local and global spatial features. First, a visual word codebook is constructed by partitioning an image into dense regions, followed by the typical k -means clustering. A locality-constrained linear coding is employed on dense regions via the visual codebook, and a spatial pyramid mat...

In visual recognition, the images are frequently modeled as unordered collections of local features (bags). We show that bag-of-words representations commonly used in conjunction with linear classifiers can be viewed as special match kernels, which count 1 if two local features fall into the same regions partitioned by visual words and 0 otherwise. Despite its simplicity, this quantization is t...

Atrous Spatial Pyramid Pooling (ASPP) is a module that can collect semantic information distributed in different scopes. However, because of the limited number sampling ranges ASPP, much valuable global features and contextual cannot be sufficiently sampled, which degrades representation ability segmentation network. Besides, due to sparse distribution effective points atrous convolution kernel...