With the rapid development of augmented reality (AR) and virtual reality (VR) technology, human-computer interaction (HCI) has been greatly improved for gaming interaction of AR and VR control. The finger micro-gesture is one of the important interactive methods for HCI applications such as in the Google Soli and Microsoft Kinect projects. However, the progress in this research is slow due to the lack of high quality public available database. In this paper, holoscopic 3D camera is used to capture high quality micro-gesture images and a new unique holoscopic 3D micro-gesture (HoMG) database is produced. The principle of the holoscopic 3D camera is based on the fly viewing system to see the objects. HoMG database recorded the image sequence of 3 conventional gestures from 40 participants under different settings and conditions. For the purpose of micro-gesture recognition, HoMG has a video subset with 960 videos and a still image subset with 30635 images. Initial micro-gesture recognition on both subsets has been conducted using traditional 2D image and video features and popular classifiers and some encouraging performance has been achieved. The database will be available for the research communities and speed up the research in this area.
The Kinect and RGB-D camera are very popular in recent years due to the benefits of Kinect and RGB-D camera that have low cost and wide availability as a sensor @cite_18 to capture gestures. However, RGB-D camera suffers from the underside artefacts such as the edge inaccuracies, low object remission and holes owning @cite_5 . The Kinect sensor offers the information of the depth measurement and create coordinates of the 3D objects. Although the abundant development toolkits can support the human body recognition, the weakness is its lacking ability to capture the flexible and robust mechanism to perform high-level gesture @cite_20 .
@cite_5 @cite_18 @cite_20
2158214532 1980867236
Common VSM (vehicle speed measurement) methods lack either necessary precision and or flexibility to be used conveniently in law enforcement applications. In this study, a new method is proposed for simultaneous camera calibration and VSM compensating for these problems. The contribution of this study is to give a solution to the degeneracy problem of the Zhang's algorithm while dealing with parallel planar patterns and using the calibration data to estimate vehicle's speed. In applications like estimating the vehicle's speed in straight roads in which the license plates are parallel to each other, the number of linearly independent equations is reduced to 2 and the method cannot be used. In this study, the degeneracy problem of the Zhang's algorithm in dealing with parallel patterns is solved. Using orthonormal properties of all rotation vectors, the number of linearly independent equations is increased from 2 to 5 and camera calibration and VSM are performed simultaneously. Results of implementing this algorithm on real images taken by law enforcement cameras show that the proposed method can estimate the vehicle's speed with a mean of errors less than 1.22 km h and consequently is proper for law enforcement applications. A controlled experiment was performed to evaluate the usability of freehand gestural target selection with different 3D marking menu layouts and target directions. We found that a rectangular layout was faster than an octagonal layout, with no significant increase in errors, and that our right-handed participants preferred to select to the right and forwards in a 3D marking menu. We propose an improved design for 3D marking menus based on our findings. The experimental results also suggest that designers should consider carefully whether or not findings from similar interaction techniques using hands-on devices can be carried over to the design of freehand gestural interaction.