Multi-cue based 3D residual network for action recognition

Neural Computing and Applications - Convolutional neural network (CNN) is a natural structure for video modelling that has been successfully applied in the field of action recognition. The existing...     

Second-order motion descriptors for efficient action recognition

Pattern Analysis and Applications - Human action recognition from realistic video data constitutes a challenging and relevant research area. Leading the state of the art we can find those methods...     

Action recognition with multi-scale trajectory-pooled 3D convolutional descriptors

Multimedia Tools and Applications - Hand-crafted and learning-based features are two main types of video representations in the field of video understanding. How to integrate their merits to design...     

基于傅立叶描绘子的步态识别

步态识别作为一种新的生物特征识别技术,通过人走路的姿势实现对个人身份的识别和认证。利用傅立叶描绘子对步态轮廓图像进行描述,用步态图像的高宽比进行步态的准周期性分析,并采用动态时间规正算法解决不同的步态周期的图像序列之间的比较问题。该算法在CMU数据库上面进行试验取得了较高的正确识别率。     

3D image retrieval based on differential geometry and co-occurrence matrix

3D image retrieval approach is a challenging problem in the research of content-based image retrieval. In this paper, a novel retrieval approach combined differential geometry and co-occurrence matrix is presented. Firstly, Gaussian curvature and mean curvature are utilized to represent the inherent characteristic of spatial surface, and then we use co-occurrence matrix to store the shape information of 3D images. Secondly, normalization process is applied to the co-occurrence matrix and the invariants independence of the translation, scaling, and rotation transforms are proved. In comparison with the recent methods, experiments indicate a lower computation complexity and a better retrieval rate to 3D images with slight different shape characteristic.     

3D Palmprint recognition using Tan and Triggs normalization technique and GIST descriptors

Multimedia Tools and Applications - The 3D palmprint biometric recognition system is being considered as a very promising way to address the limitations of 2D palmprint recognition systems. This...     

Real-time 2D+3D facial action and expression recognition

This paper presents a completely automated facial action and facial expression recognition system using 2D+3D images recorded in real-time by a structured light sensor. It is based on local feature tracking and rule-based classification of geometric, appearance and surface curvature measurements. Several experiments conducted under relatively non-controlled conditions demonstrate the accuracy and robustness of the approach.     

Motion recognition using nonparametric image motion models estimated from temporal and multiscale co-occurrence statistics

A new approach for motion characterization in image sequences is presented. It relies on the probabilistic modeling of temporal and scale co-occurrence distributions of local motion-related measurements directly computed over image sequences. Temporal multiscale Gibbs models allow us to handle both spatial and temporal aspects of image motion content within a unified statistical framework. Since this modeling mainly involves the scalar product between co-occurrence values and Gibbs potentials, we can formulate and address several fundamental issues: model estimation according to the ML criterion (hence, model training and learning) and motion classification. We have conducted motion recognition experiments over a large set of real image sequences comprising various motion types such as temporal texture samples, human motion examples, and rigid motion situations.     

A new approach for physical human activity recognition based on co-occurrence matrices

The Journal of Supercomputing - In recent years, it has been observed that many researchers have been working on different areas of detection, recognition and monitoring of human activities. The...     

Comparative analysis of shape descriptors for 3D objects

Multimedia Tools and Applications - One of the basic characteristics of an object is its shape. Several research areas in mathematics and computer science have taken an interest in object...