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We present a new descriptor for tactile 3D object classification. It is invariant to object movement and simple to construct, using only the relative geometry of points on the object surface. We demonstrate successful classification of 185 objects in 10 categories, at sparse to dense surface sampling rate in point cloud simulation, with an accuracy of 77.5% at the sparsest and 90.1% at the densest...
In this paper, we propose a robust multi-object tracking algorithm for acquiring object oriented multi-angle videos, which takes advantages of two different tracking techniques represented by subdivided color histogram based tracking and labeling based tracking. Object models based on color histograms are further subdivided to differentiate similar color regions. Another tracking technique utilizes...
Object representation is one of the most challenging tasks in robotics because it must provide reliable information in real-time to enable the robot to physically interact with the objects in its environment. To ensure reliability, a global object descriptor must be computed based on a unique and repeatable object reference frame. Moreover, the descriptor should contain enough information enabling...
This paper presents an enhanced version of descriptor DPM-BCF (Depth Projection Maps-based Bag of Contour Fragments). Named as eDPM, it modified the projection method by converting the depth cloud into three grayscale projected maps in three orthogonal planes. Then we extract Bag of Contour Fragments (BCF) descriptor and Histogram of Oriented Gradient (HOG) descriptor from the three grayscale projected...
In this paper, we propose an image target tracking algorithm for an embedded platform. Our proposed can process 1280 × 720 resolution video sequences and provide accurate image tracking in real time. In the tracking algorithm, an adaptive local edge detection method is employed to extract the feature pixels of a tracked object. To reduce tracking errors, a region-based local binary pattern feature...
Robust and accurate visual tracking is needed for many computer vision applications from video summarization to visual surveillance. Visual tracking remains to be a challenging task because of factors such as changing object appearance, illumination variations and shadows, partial and full occlusions, camera motion, distractors, and scale changes. Recently our group proposed a Likelihood of Features...
Accurate and efficient object tracking is an important aspect of various security and surveillance applications. In object tracking solutions which utilize intensity-based histogram feature methods for use on wide area motion imagery (WAMI), there currently exists tracking challenges due to object structural information distortions and pavement/background variations. The inclusion of structural target...
Improved Completed Robust Local Binary Pattern is one of the robust texture extraction for image retrieval that rotation invariant (ICRLBP). ICRLBP has proven that can increase the precision, recall, and computation time from its previous work by 21.14%, 20.03%, and 56 times, respectively, on four different texture image dataset. ICRLBP, however, has a lot of feature, thus require more time during...
The image's histogram represents the statistical feature of distribution of pixels and is not related to the specific positions of pixels. This feature gives histogram-based algorithms the ability to resist geometric attacks, but the embedding capacity is limited. In this paper we combine two typical histogram-based functions and give two relationships to three bins in a group. So the embedding capacity...
In order to improve the docking success rate in Automated Aerial Refueling (AAR), it is important to identify the receiver aircraft's receptacle for boom receptacle refueling (BRR). Meanshift tracking algorithm only considers the H component color statistics of the target area, lacking spatial information, could easily lead to inaccurate tracking. Besides, Meanshift tracking algorithm could easily...
The image's histogram use the statistical features of an image and is regardless of the specific distribution of image pixels. With this feature, the histogram-based image watermark algorithm can avoid the desynchronization that geometric attacks bring to image and is robust to geometric attacks. Typical histogram algorithms can resist translation and crop attacks, but the ability to resist rotation,...
Tracking the object with stable features is an important and challenging task in real scenes where the object appearance constantly changes or is disturbed by the background etc. In this paper, a novel frame work of object representation and tracking based on stable feature mining is presented. Firstly, the object region is adaptively detected and then the peak contour of V color component histogram...
In this paper, an improved scale-invariant feature transform (SIFT) algorithm for synthetic aperture radar (SAR) image matching is proposed. Initially, feature descriptors based on gradient ratio (GR) are constructed by utilizing traditional SIFT method. In order to measure the matching degree between images, the similarities of the descriptors are then calculated via the symmetry kullback-leibler...
Lung segmentation is an important first step towards an automated CAD (Computer Aided Detection) system for a variety of medical applications. These applications range from lung nodule detection for identifying cancerous tumors to acinar shadow detection for identifying Tuberculosis. In our prior work we had used the Concave Hull algorithm for lung segmentation. However, our results showed over segmentation...
This paper presents an iterative motion estimation and error evaluation method for efficient occlusion detection. From a pair of reference and target images, the proposed method detects occlusions using four steps: (i) pre-processing for robust motion estimation, (ii) detection of candidates for the occlusion, (iii) one-dimensional motion estimation, and (iv) motion evaluation and update in the target...
This paper presents a complete framework aimed to nondestructive inspection of composite materials. Starting from the acquisition, performed with lock-in thermography, the method flows through a set of consecutive blocks of data processing: input enhancement, feature extraction, classification and defect detection. Experimental results prove the capability of the presented methodology to detect the...
The detection of abrupt shot boundary is a fundamental task of video analytics and content-based video retrieval. The traditional methods tend to take much time in frame processing. In this paper, a GPU-accelerated abrupt shot boundary detection algorithm is proposed. This algorithm takes into account of both global feature and local feature of the video frames, in which the block HSV histograms and...
Recent studies showed the potential of the Phase Based Motion Estimator when applied to ultrasound images containing transverse oscillations. Even though the emergence of ultrafast or high frame rates imaging overcame some of the prior limitations of the algorithm regarding its capability to detect large displacement values, the method still presents an important lack of robustness. In this paper,...
Motion vectors histogram (MVH) is an effective feature vector in video indexing and analysis applications. One of the challenges in the use of motion vector histogram is that it is not robust to video aspect ratio (AR). As a result, it is not suitable for comparing videos with different ARs. In this paper a feature vector based on motion vectors in H.264/AVC is introduced which is robust to variations...
Person re-identification in camera network, with non-overlapping fields of view based on descriptive features is an important task in surveillance systems. In general, the person re-identification aims to recognize an individual through different pictures by measuring the similarity between two individuals.
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