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For intelligent vehicle applications, detecting pedestrian technique must be robust and perform in real time. In pedestrian detection, support vector machine (SVM) is one of the popular classifiers because of its robust performance. In this paper, we propose the new method to implement cascade SVM that enables fast rejection of negative samples. The proposed method is tested with INRIA person dataset...
The permutation coding neural classifier (PCNC) and its application to face recognition are described. Face recognition is a very important task in security applications such as those in airports and other institutions and for authentication via photo tagging in social networks. It is possible to improve face recognition with the PCNC using special types of distortion applied to the original images...
The mammalian visual system is uniquely capable of robustly recognizing objects in its field of view regardless of their orientation, scale, or position, while learning new objects from a small number of training examples and generalizing robustly to a broad class of visually similar objects. The cortical structures that implement the visual system have been successfully emulated in several biologically-inspired...
Automatic facial expression recognition plays an important role in agent-based interface development and datadriven animation. This paper presents an intelligent facial action and emotion recognition system for a humanoid robot. Motivated by the Facial Action Coding System, this research focuses on the recognition of seven basic emotions and 18 Action Units (AU). Since effective facial representations...
Generating the descriptive sentences of a real image is a challenging task in image understanding. The difficulty mainly lies in recognizing the interaction activities between objects, and predicting the relationship between objects and stuff/scene. In this paper, we propose a framework for improving image description generation by addressing the above problems. Our framework mainly includes two models:...
Automatically discovering and recognizing the main structured visual pattern of an image is a challenging problem. The most difficulties are how to find the component objects and how to recognize the interaction among these objects. The component objects of the structured visual pattern have consistent 3D spatial co-occurrence layout across images, which manifest themselves as a predictable pattern...
Off-line automatic assessment systems can be an aid for teachers in the marking process. There has been no recent work in the development of off-line automatic assessment systems using handwriting recognition, even though such systems will clearly benefit the education sector. The reason is many schools and universities in many parts of the world still use paper-based examination. This research proposes...
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