Hand posture understanding is essential to human robot interaction. The existing hand detection approaches using a Viola-Jones detector have two fundamental issues, the degraded performance due to background noise in training images and the in-plane rotation variant detection. In this paper, a hand posture recognition system using the discrete Adaboost learning algorithm with Lowe’s scale invar...

In this paper constrained contour models are applied for hand posture recognition in single color images. In particular, the proposed algorithm utilizes a class of physics-based modelling methods called Deformable Templates [1],[2],[3]. After colorbased image segmentation a contour hypothesis is detected and some features are extracted, suitable for comparison with the template’s geometric prop...

Activity recognition plays a key role in providing information for context-aware applications. When attempting to model activities, some researchers have looked towards Activity Theory, which theorizes that activities have objectives and are accomplished through tools and objects. The goal of this paper is to determine if hand posture can be used as a cue to determine the types of interactions ...

This paper introduces a fast and feasible method for the collection of hand gesture samples. Currently, there are not solid reference databases and standards for the evaluation and comparison of developed algorithms in hand posture recognition, and more generally in gesture recognition. These are two important issues that should be solved in order to improve research results. Unlike previous ha...

system [6] is defined for each finger. Recently, the model-based hand posture analysis researches have become increasingly popular for many applications, such as hand gesture recognition, intelligent human-machine interface, virtual reality, and computer animation. However, the main problems that make the conventional marker-based hand posture analysis system inapplicable are inefficient calcul...

In this paper, we address the problem of hand posture recognition with a binocular camera. As bare hand has a few landmarks for matching, instead of using accurate matching between two views, we define a kind of mapping score–Disparity Cost Map. The disparity cost map serves as the final hand representation for recognition. As we use the disparity cost map, an explicit segmentation stage is not...

In this paper, we propose to investigate the role of a new descriptor named Kernel Descriptor (KDES), recently introduced in 1 for hand posture recognition. As the hand posture has it own the color characteristic, we will examine kernel descriptor in diffident color channels such as HSV, RGB, Lab to find out the most suitable color space for kernel representation of hand posture. We perform ext...

We propose a new method for hand gesture recognition via sparse representation. Initially, we present the region of the hand is detected based on skin color segmentation in the YCbCr color space and image normalization. Then, the recognition of hand posture is casted as the sparse representation of a test image with a set of the database images. The l1minimization is applied to accurately and e...

This paper surveys a new research field of object behavior classification using sequential syntactic pattern recognition, which recognizes high-level object behaviors while in parallel recovering from low-level object recognition classification errors. A new approach of syntactical object behavior classification with a robust implementation is introduced. It is an innovative approach that requi...