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Trajectories extracted by previous methods for human action recognition contain irrelevant changes, and the Orientation-Magnitude descriptors of their shapes lack the robustness to camera motion. To solve these problems, action recognition by tracking salient relative motion points is proposed in this paper. Firstly, motion boundary detector which suppresses the camera constant motion is utilized...
Although a great success has been achieved on action detection tasks by using "bag of features" architecture as video representations, action detection with web camera still remains a challenge. Most of these algorithms can extract features either sparsely at interest points or densely on regular grids, usually, sampling densely can get better results than sampling sparsely using the local...
The process of image tampering is nothing but digital process that needs the knowledge good visual creativity as well as image properties. There are different kinds of image tampering such as copy & move, splicing, resize, cropping etc. In this paper we are focusing on blurred image splicing. The image splicing is done for many reasons, the most critical impacts of image splicing related to security...
It was proved that the fusion of information from multi-modality images increases the accuracy of pedestrian recognition systems. One of the best approache so far is to concatenate the features from multi-modality images into a large feature vector, but it requires strong camera calibration settings and non-discriminative modalities could lead to missclassification of some particular images. We present...
Robust fingertip force detection from fingernail image is a critical strategy that can be applied in many areas. However, prior research fixed many variables that influence the finger color change. This paper analyzes the effect of the finger joint on the force detection in order to deal with the constrained finger position setting. A force estimator method is designed: a model to predict the fingertip...
The goal of video summarization is to turn large volume of video data into a compact visual summary that can be easily interpreted by users in a while. Existing summarization strategies employed the point based feature correspondence for the superframe segmentation. Unfortunately, the information carried by those sparse points is far from sufficiency and stability to describe the change of interesting...
The task of matching persons across non-overlapping camera views, known as person re-identification, is rather challenging due to strong visual similarity and large appearance changes caused by illumination, pose and occlusion. Most approaches rely on low-level features that are both discriminative and invariant. In this work, we propose a novel method to address this problem by fusing mid-level semantic...
In this paper, we present an approach for multicamera pedestrian detection exploiting the concepts of multiview geometry and the shapes of 3D geometric primitives. Multicamera occupancy maps provide peak responses corresponding to the object detection but suffer from several false detections known as ghosts. The novelty of this paper is the introduction of shape patterns which can model the objects,...
In this paper, we propose a new strategy for near-duplicate video retrieval that is based on shot aggregation. We investigate different methods for shot aggregation with the main objective to solve the difficult trade-off between performance, scalability and speed. The proposed short aggregation is based on two steps. The first step consists of keyframes selection. And the second one is the aggregation...
Of increasing interest to the computer vision community is to recognize egocentric actions. Conceptually, an egocentric action is largely identifiable by the states of hands and objects. For example, “drinking soda” is essentially composed of two sequential states where one first “takes up the soda can”, then “drinks from the soda can”. While existing algorithms commonly use manually defined states...
Non-uniform camera shake removal is a knotty problem which plagues the researchers due to the huge computational cost of high-dimensional blur kernel estimation. To address this problem, we propose an acceleration method to compute the 3D projection of 2D local blur kernels fast, and then derive the 3D kernel by interpolating from a minimal set of local blur kernels. Under this scheme, a perpendicular...
This study proposes a symmetry-based forward vehicle detection and collision warning system (FCW) on smartphone. The proposed system identifies forward vehicle by shadow with vehicular symmetry. Through Bayes classifier tracking approach, it can reduce the error detection of image processing. Shadow detection with symmetry-based approach could improve the robustness of identifying forward vehicle...
This work addresses the problem of automatic wire recognition in images obtained from an unmanned aerial vehicle (UAV). As wires are thin structures it is difficult to extract particular pixels eliminating background. We propose the method that allows detecting wires and estimating their parameters without any human intervention.
In this paper, we propose a novel kernel function for recognizing objects in RGB-D egocentric videos. In order to effectively exploit the varied object appearance in a video, we take a set-based recognition approach and represent the target object using the set of frames contained in the video. Our kernel function measures the similarity of two sets by the minimum distance between the sparse affine...
In a spliced blurred image, the spliced region and the original image may have different blur types. Splicing localization in this image is challenging when a forger uses image resizing as anti-forensics to remove the splicing traces anomalies. In this paper, we overcome this problem by proposing a method for splicing localization based on partial blur type inconsistency. In this method, after the...
This paper presents a depth map restoration scheme for both the raw and projected depth map from Kinect v2 sensor. Based on IR-depth consistency, erroneous depth readings around foreground objects are removed by an edge aware consistency correction method. Moreover, a joint adaptive kernel regression algorithm is designed to upsample the sparse depth map after the projection from Kinect v2 sensor's...
This 1-Page Demonstration paper is included in the track “Multimedia Systems and Applications”. The work has been already published in [1] and [2]. The main idea of the demonstration is to show how the Virtual Architecture ARTICo3 works within a high performance wireless sensor node called HiReCookie. The selected demo includes an image processing application with several filters running as different...
Classically Visual servoing considered the regulation in the image of a set of visual features (usually geometric features). Recently direct visual servoing scheme, such as photometric visual servoing, have been introduced in order to consider every pixel of the image as a primary source of information and thus avoid the extraction and the tracking of such geometric features. Previous works proposed...
Real-time dense computer vision and SLAM offer great potential for a new level of scene modelling, tracking and real environmental interaction for many types of robot, but their high computational requirements mean that use on mass market embedded platforms is challenging. Meanwhile, trends in low-cost, low-power processing are towards massive parallelism and heterogeneity, making it difficult for...
To reduce the manpower and response time for surveillance systems at low cost, in this paper, an ARM-based embedded system dedicated for unattended realtime moving target detection is constructed. The comprehensive procedures in building up an embedded system such as setup environment for cross-compilation, migration of Bootloader, migration of Linux-2.6 kernel, fabrication and migration of root document...
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