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A new approach to speed up in action recognition based on key-frame extraction

A new approach to speed up in action recognition based on ke...

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Iranian Machine vision and Image Processing (MVIP)

作者： Neda Azouji Zohreh Azimifar Computer Vision and Pattern Recognition Lab Shiraz University Shiraz Iran

Human action recognition is the process of labeling videos contain human motion with action classes. The run time complexity is one of the most important challenges in action recognition. In this paper, we address this problem using video abstraction techniques including key-frame extraction and video skimming. At first we extract key-frames and then skim the video clip by concatenating excerpts around the selected key-frames. This shorter sequence is used as input for classifier. Our proposed approach not only reduces the space complexity but also reduces the run time in both train and test steps. The experimental results provided on KTH action datasets show that the proposed method achieves good performance without losing considerable classification accuracy.

关键词： Videos Feature extraction Accuracy Image color analysis Shape Support vector machines computer vision

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Heterogeneous Auto-similarities of Characteristics (HASC): Exploiting Relational Information for Classification

Heterogeneous Auto-similarities of Characteristics (HASC): E...

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International Conference on computer vision (ICCV)

作者： Marco San Marco Crocco Marco Cristani Samuele Martelli Vittorio Murino Pattern Analysis & Computer Vision Istituto Italiano di Tecnologia Genova Italy

Capturing the essential characteristics of visual objects by considering how their features are inter-related is a recent philosophy of object classification. In this paper, we embed this principle in a novel image descriptor, dubbed Heterogeneous Auto-Similarities of Characteristics (HASC). HASC is applied to heterogeneous dense features maps, encoding linear relations by co variances and nonlinear associations through information-theoretic measures such as mutual information and entropy. In this way, highly complex structural information can be expressed in a compact, scale invariant and robust manner. The effectiveness of HASC is tested on many diverse detection and classification scenarios, considering objects, textures and pedestrians, on widely known benchmarks (Caltech-101, Brodatz, Daimler Multi-Cue). In all the cases, the results obtained with standard classifiers demonstrate the superiority of HASC with respect to the most adopted local feature descriptors nowadays, such as SIFT, HOG, LBP and feature co variances. In addition, HASC sets the state-of-the-art on the Brodatz texture dataset and the Daimler Multi-Cue pedestrian dataset, without exploiting ad-hoc sophisticated classifiers.

关键词： Electromagnetic interference Feature extraction Joints Histograms Noise Mutual information Entropy

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Is It Time to Rethink Motion Artifacts? Temporal Relationships between Electrodermal Activity and Body Movements in Real-Life Conditions

Is It Time to Rethink Motion Artifacts? Temporal Relationshi...

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International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII

作者： Ryad Chellali Shannon Hennig Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia (IIT) Genova Italy

This work investigates the temporal dynamics between electro dermal activity (EDA) and gestures during real-life public speaking. Wrist movements and EDA were recorded from speakers during a high-stakes public speaking event. The extreme values theory, more typically used for detecting relatively rare events in financial markets or flood calculations, was adapted and combined with continuous wavelet transform to automatically detect significant temporal events from the derivatives of the movement and EDA time series. The literature describing motion artifacts in EDA predicts that detected movement events should precede or co-occur with EDA. In contrast, we also observed a second case in which EDA changes preceded movement (approximately 40% of cases). These results suggest that humans may move or gesture in response to affective changes, which has clear implications for anyone studying arousal and gesture 'in the wild.

关键词： Time series analysis Shape Skin Continuous wavelet transforms Sensors

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Adaptive and safe mobile manipulator for human robot interaction

Adaptive and safe mobile manipulator for human robot interac...

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IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RIISS

作者： Amal Meddahi Ryad Chellali Pattern Analysis and Computer Vision Laboratory Istituto Italiano di Tecnologia Università degli Studi di Genova Genova Italy Pattern Analysis and Computer Vision Laboratory Istituto Italiano di Tecnologia Genova Italy

Mobile robotic manipulators will be more and more present in our daily life. Many applications use already these platforms such as for homecare, industrial logistics, etc. and most of the time with in vicinity of humans, within dynamic and unknown environments. This poses the problem of adaptability and safety: robots should adapt to support a wide range of human users behaviors, with a strong guaranty of users' safety. In addition, such functions should take place with environments that are dynamic and not known a priori. This contribution reports on the mobile manipulator we are developing. We focus on solving the safe path planning problem for both the robot base and the robot manipulator in the presence of humans and dynamic obstacles: a safety distance should be strictly maintained by the robot with regard to the person involved in the interactive task as well as with any other person or moving object potentially colliding with the robot while performing the assigned task. These two requirements are achieved in real time by a multi-objective optimization that controls the base and the manipulator based on the task definition and the sensing data provided by the embedded sensors. Simulated scenarios have been tested and the obtained results are presented and discussed.

关键词： Robot kinematics Mobile communication Robot sensing systems Manipulator dynamics Mobile robots

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Temporal Poselets for Collective Activity Detection and Recognition

Temporal Poselets for Collective Activity Detection and Reco...

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International Conference on computer vision Workshops (ICCV Workshops)

作者： Moin Nabi Alessio Del Bue Vittorio Murino Pattern Analysis and Computer Vision (PAVIS) Istituto Italiano di Tecnologia (IIT) Genova Italy

Detection and recognition of collective human activities are important modules of any system devoted to high level social behavior analysis. In this paper, we present a novel semantic-based spatio-temporal descriptor which can cope with several interacting people at different scales and multiple activities in a video. Our descriptor is suitable for modelling the human motion interaction in crowded environments - the scenario most difficult to analyse because of occlusions. In particular, we extend the Pose let detector approach by defining a descriptor based on Pose let activation patterns over time, named TPOS. We will show that this descriptor can effectively tackle complex real scenarios allowing to detect humans in the scene, to localize (in space-time) human activities, and perform collective group activity recognition in a joint manner, reaching state-of-the-art results.

关键词： Detectors Feature extraction Video sequences Vectors Context Semantics Torso

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A new method for sclera vessel recognition using OLBP

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2012 International Conference on Service-Oriented Computing, ICSOC 2012

作者： Das, Abhijit Pal, Umapada Ferrer Ballester, Miguel A. Blumenstein, Michael Institute for Integrated and Intelligent Systems Griffith University QLD Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India IDeTIC University of Las Palmas de Gran Canaria Las Palmas Spain

ISBN: (纸本)9783319029603

This paper proposes a new sclera vessel recognition technique. The vessel patterns of sclera are unique for each individual and this can be utilized to identify a person uniquely. In this research we have used a time adaptive active contour-based region growing technique for sclera segmentation. Prior to that, we have made some tonal and illumination correction to get a clearer sclera area without the distributing vessel structure. This is because the presence of complex vessel structures occasionally affects the region-growing process. The sclera vessels are not prominent in the images, so in order to make them clearly visible, a local image enhancement process using a Haar high pass filter is incorporated. To get the total orientation of the vessels, we have used Orientated Local Binary pattern (OLBP). The OLBP images of each class are used for template matching for classification by calculating the minimum Hamming Distance. We have used the UBIRIS version 1 dataset for the experimentation of our research. The proposed approach has achieved high recognition accuracy employing the above-mentioned dataset. © Springer International Publishing 2013.

关键词： Local binary pattern

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SVM and nn based offline signature verification

SVM and nn based offline signature verification

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作者： Pal, Srikanta Alaei, Alireza Pal, Umapada Blumenstein, Michael School of Information and Communication Technology Gold Coast Griffith University Australia Polytech'Tours Université François-Rabelais de Tours France Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Among all of the biometric authentication systems, handwritten signatures are considered as the most legally and socially accepted attributes for personal verification. The objective of this paper is to present an empirical contribution toward the understanding of a threshold-based signature verification technique involving off-line Bangla (Bengali) signatures. Experiments on signature verification concerning non-English signatures are an important consideration in the signature verification area. Only very few research works employing signatures of Indian script have been considered in the field of non-English based signature verification. To fill this gap, a threshold-based scheme for the verification of off-line Bangla signatures is proposed. Some techniques such as under-sampled bitmap, intersection/end point and directional chain code are employed for feature extraction. The thresholds are computed based on the similarity measures obtained employing the nearest neighbor classifier. The SVM classifier has also been considered for mainly comparative experimental result generation. Furthermore, a Bangla signature database, which consists of 2400 (100 × 24) genuine signatures and 3000 (100 × 30) forgeries, has been created and is employed for experimentation. An average error rate (AER) of 12.33% was obtained as the best verification result using directional chain code features in this research work. As a comparative study, a different dataset (GPDS-160) has also been considered. © 2013 Imperial College Press.

关键词： Codes (symbols)

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Trusting Skype: Learning the Way People Chat for Fast User Recognition and Verification

Trusting Skype: Learning the Way People Chat for Fast User R...

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International Conference on computer vision Workshops (ICCV Workshops)

作者： Giorgio Roffo Marco Cristani Loris Bazzani Hà Quang Minh Vittorio Murino Department of Computer Science University of Verona Verona Pattern Analysis & Computer Vision Istituto Italiano di Tecnologia Genova

Identity safekeeping on chats has recently become an important problem on social networks. One of the most important issues is identity theft, where impostors steal the identity of a person, substituting her in the chats, in order to have access to private information. In the literature, the problem has been addressed by designing sets of features which capture the way a person interacts through the chats. However, such approaches perform well only on the long term, after a long conversation has been performed, this is a problem, since in the early turns of a conversation, much important information can be stolen. This paper focuses on this issue, presenting a learning approach which boosts the performance of user recognition and verification, allowing to recognize a subject with considerable accuracy. The proposed method is based on a recent framework of one-shot multi-class multi-view learning, based on Reproducing Kernel Hilbert Spaces (RKHS) theory. Our technique reaches a recognition rate of 76.9% in terms of AUC of the Cumulative Matching Characteristic curve, with only 10 conversational turns considered, on a total of 78 subjects. This sets the new best performances on a public conversation benchmark.

关键词： Kernel Probes Feature extraction Vectors Training Testing Accuracy

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A distributed multi robot SLAM system for environment learning

A distributed multi robot SLAM system for environment learni...

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IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RIISS

作者： Syed Riaz un Nabi Jafri Ryad Chellali Pattern Analysis and Computer Vision (PAVIS) Laboratory Istituto Italiano di Tecnologia Universita degli Studi di Genova Genova Italy Pattern Analysis and Computer Vision (PAVIS) Laboratory Istituto Italiano di Tecnologia Genova Italy

This paper presents a multi mobile robot simultaneous localization and mapping (SLAM) system for feature based environment learning by using team of exploring robots. The environmental information is measured through the dynamic sensor network in the shape of moving robots with unknown initial poses. Each robot is equipped with 2D laser scanner and a webcam and it serves as a moving sensor node to perceive horizontal and vertical line features respectively. All the moving nodes are responsible to build the informational structured space. The proposed system is using a unified Extended Kalman Filter (EKF) based SLAM framework for each robot which eventually builds a line feature based partial 3D model of the environment. Each moving robotic sensor node then shares its feature based map model to other moving nodes which are in communication range. A global map model is then transformed after getting mutual pose estimation of the robots by matching mutual common map features in addition by taking visual confirmation of other robot. The proposed system has been tested in an indoor environment and results are shown in the paper.

关键词： Simultaneous localization and mapping Cameras Feature extraction Lasers Robot vision systems

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Robust object tracking in crowd dynamic scenes using explicit stereo depth

Robust object tracking in crowd dynamic scenes using explici...

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11th Asian Conference on computer vision, ACCV 2012

作者： Li, Chi Lu, Le Hager, Gregory D. Tang, Jianyu Wang, Hanzi Cognitive Science Department Xiamen University Xiamen China Imaging and Computer Vision Siemens Corporate Research Princeton NJ United States Computer Science Department Johns Hopkins University Baltimore MD United States Center for Pattern Analysis and Machine Intelligence Xiamen University China

ISBN: (纸本)9783642374302

In this paper, we exploit robust depth information with simple color-shape appearance model on single object tracking in crowd dynamic scenes. Since binocular video streams are captured from a moving camera rig, background subtraction cannot provide a reliable enhancement of region of interest. Our main contribution is a novel tracking strategy to employ explicit stereo depth to track and segment object in crowd dynamic scenes with occlusion handling. Appearance cues including color and shape play a secondary role to further extract the foreground acquired by previous depth-based segmentation. The proposed depth-driven tracking approach can largely alleviate the drifting issue, especially when the object frequently interacts with similar background in long sequence tracking. The problems caused by rapid object appearance change can also be avoided due to the stability of the depth cue. Furthermore, we propose a new, yet simple and effective depth-based scheme to cope with complete occlusion in tracking. From experiments on a large collection of challenging outdoor and indoor sequences, our algorithm demonstrates accurate and reliable tracking performance which outperforms other state-of-the-art competing algorithms. © 2013 Springer-Verlag.

关键词： Image segmentation

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