Numerous tracking-by-detection methods have been proposed for robust visual tracking, among which compressive tracking (CT) has obtained some promising results. A scale-adaptive CT method based on multifeature integration is presented to improve the robustness and accuracy of CT. We introduce a keypoint-based model to achieve the accurate scale estimation, which can additionally give a prior location of the target. Furthermore, by the high efficiency of data-independent random projection matrix, multiple features are integrated into an effective appearance model to construct the naïve Bayes classifier. At last, an adaptive update scheme is proposed to update the classifier conservatively. Experiments on various challenging sequences demonstrate substantial improvements by our proposed tracker over CT and other state-of-the-art trackers in terms of dealing with scale variation, abrupt motion, deformation, and illumination changes.
The description of local surface features is a critical step in surface matching and object recognition. We present a descriptor for three-dimensional shapes based on the bispectrum of spherical harmonics (BSH). First, points in a support region of a feature point are used to construct a local reference frame, and a histogram is formed by accumulating the points falling within each bin in the support region. Second, spherical harmonic coefficients of the histogram and its bispectrum are calculated. Finally, the feature descriptor is obtained via principal component analysis. We tested our BSH descriptor on public datasets and compared its performance with that of several existing methods. The results of our experiments show that the proposed descriptor outperforms other methods under various noise levels and mesh resolutions.
Liquid crystal optical phased array (LCOPA) is a kind of spatial light modulator(SLM) which is now widely studied in the field of laser radar, adaptive optics, optical information processing, etc. The calibration of the voltage-phase characteristic of a LCOPA is an important step which will seriously affect the performance of a LCOPA. Firstly, derived the relationship between the phase distribution of the emergent light and light intensity in the far-field. Designed an optic path to calibrate the voltage-phase characteristic. And built up a observation equation. Introduced a weight matrix to reduce the errors caused by the impact of phenomena such as the fly-back. Proposed a new calibration algorithm based on the measurement of light intensity. A checkerboard pattern with a period of M pixels per check was used in the calibration routine. Fix the control voltage of one region, and change the voltage in another region. The light pattern in the far-field changes with the control voltage. Measure the intensity of the light beam at the center of the far-field. Then, obtain the raw data. Filter and normalize the raw data. And calculate the phase difference between two regions. Use weighted least square method to get the relationship between the control voltage and the phase retardation. Lastly, using this method to calibrate a LCOPA which is produced by BNS corp.
Scanning Laser Radar has been widely used in many military and civil areas. Usually there are relative movements between the target and the radar, so the moving target image modeling and simulation is an important research content in the field of signal processing and system design of scan-imaging laser radar. In order to improve the simulation speed and hold the accuracy of the image simulation simultaneously, a novel fast simulation algorithm is proposed in this paper. Firstly, for moving target or varying scene, an inequation that can judge the intersection relations between the pixel and target bins is obtained by deriving the projection of target motion trajectories on the image plane. Then, by utilizing the time subdivision and approximate treatments, the potential intersection relations of pixel and target bins are determined. Finally, the goal of reducing the number of intersection operations could be achieved by testing all the potential relations and finding which of them is real intersection. To test the method’s performance, we perform computer simulations of both the new proposed algorithm and a literature’s algorithm for six targets. The simulation results show that the two algorithm yield the same imaging result, whereas the number of intersection operations of former is equivalent to only 1% of the latter, and the calculation efficiency increases a hundredfold. The novel simulation acceleration idea can be applied extensively in other more complex application environments and provide equally acceleration effect. It is very suitable for the case to produce a great large number of laser radar images.