Search Results - "2007 IEEE Conference on Advanced Video and Signal Based Surveillance"

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  1. 1

    Scream and gunshot detection and localization for audio-surveillance systems by Valenzise, G., Gerosa, L., Tagliasacchi, M., Antonacci, F., Sarti, A.

    “…This paper describes an audio-based video surveillance system which automatically detects anomalous audio events in a public square, such as screams or…”
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    Conference Proceeding
  2. 2

    ETISEO, performance evaluation for video surveillance systems by Nghiem, A.T., Bremond, F., Thonnat, M., Valentin, V.

    “…This paper presents the results of ETISEO, a performance evaluation project for video surveillance systems. Many other projects have already evaluated the…”
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    Conference Proceeding
  3. 3

    CASSANDRA: audio-video sensor fusion for aggression detection by Zajdel, W., Krijnders, J.D., Andringa, T., Gavrila, D.M.

    “…This paper presents a smart surveillance system named CASSANDRA, aimed at detecting instances of aggressive human behavior in public environments. A…”
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    Conference Proceeding
  4. 4

    Detection of temporarily static regions by processing video at different frame rates by Porikli, F.

    “…This paper presents an abandoned item and illegally parked vehicle detection method for single static camera video surveillance applications. By processing the…”
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    Conference Proceeding
  5. 5

    Enhancing the spatial resolution of presence detection in a PIR based wireless surveillance network by Zappi, P., Farella, E., Benini, L.

    “…Pyroelectric sensors are low-cost, low-power small components commonly used only to trigger alarm in presence of humans or moving objects. However, the use of…”
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    Conference Proceeding
  6. 6

    Acoustic Doppler sonar for gait recogination by Kalgaonkar, K., Raj, B.

    “…A person's gait is a characteristic that might be employed to identify him/her automatically. Conventionally, automatic for gait-based identification of…”
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    Conference Proceeding
  7. 7

    Stationary objects in multiple object tracking by Guler, S., Silverstein, J.A., Pushee, I.H.

    “…This paper presents an approach to detect stationary foreground objects in naturally busy surveillance video scenes with several moving objects. Our approach…”
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    Conference Proceeding
  8. 8

    Stationary target detection using the objectvideo surveillance system by Venetianer, P.L., Zhang, Z., Yin, W., Lipton, A.J.

    “…Detecting stationary objects, such as an abandoned baggage or a parked vehicle is crucial in a wide range of video surveillance and monitoring applications…”
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    Conference Proceeding
  9. 9

    Detection of abandoned objects in crowded environments by Bhargava, M., Chia-Chih Chen, Ryoo, M.S., Aggarwal, J.K.

    “…With concerns about terrorism and global security on the rise, it has become vital to have in place efficient threat detection systems that can detect and…”
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    Conference Proceeding
  10. 10

    Camera selection in visual sensor networks by Soro, S., Heinzelman, W.

    “…Wireless networks of visual sensors have recently emerged as a new type of sensor-based intelligent system, with performance and complexity challenges that go…”
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    Conference Proceeding
  11. 11

    Detection of abnormal behaviors using a mixture of Von Mises distributions by Calderara, S., Cucchiara, R., Prati, A.

    “…This paper proposes the use of a mixture of Von Mises distributions to detect abnormal behaviors of moving people. The mixture is created from an unsupervised…”
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    Conference Proceeding
  12. 12

    What are customers looking at? by Xiaoming Liu, Krahnstoever, N., Ting Yu, Tu, P.

    “…Computer vision approaches for retail applications can provide value far beyond the common domain of loss prevention. Gaining insight into the movement and…”
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    Conference Proceeding
  13. 13

    A fast algorithm for adaptive background model construction using parzen density estimation by Tanaka, T., Shimada, A., Arita, D., Taniguchi, R.

    “…Non-parametric representation of pixel intensity distribution is quite effective to construct proper background model and to detect foreground objects…”
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    Conference Proceeding
  14. 14

    Camera tamper detection using wavelet analysis for video surveillance by Aksay, A., Temizel, A., Enis Cetin, A.

    “…It is generally accepted that video surveillance system operators lose their concentration after a short period of time and may miss important events taking…”
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    Conference Proceeding
  15. 15

    Video analytics for retail by Senior, A.W., Brown, L., Hampapur, A., Shu, C.-F., Zhai, Y., Feris, R.S., Tian, Y.-L., Borger, S., Carlson, C.

    “…We describe a set of tools for retail analytics based on a combination of video understanding and transaction-log. Tools are provided for loss prevention…”
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    Conference Proceeding
  16. 16

    Improved One-class SVM Classifier for Sounds Classification by Rabaoui, A., Davy, M., Rossignol, S., Lachiri, Z., Ellouze, N.

    “…This paper proposes to apply optimized one-class support vector machines (1-SVMs) as a discriminative framework in order to address a specific audio…”
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    Conference Proceeding
  17. 17

    Model-based human posture estimation for gesture analysis in an opportunistic fusion smart camera network by Chen Wu, Aghajan, H.

    “…In multi-camera networks rich visual data is provided both spatially and temporally. In this paper a method of human posture estimation is described…”
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    Conference Proceeding
  18. 18

    Dense disparity estimation from omnidirectional images by Arican, Z., Frossard, P.

    “…This paper addresses the problem of dense estimation of disparities between omnidirectional images, in a spherical framework. Omnidirectional imaging certainly…”
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    Conference Proceeding
  19. 19

    Learning gender from human gaits and faces by Caifeng Shan, Shaogang Gong, McOwan, P.W.

    “…Computer vision based gender classification is an important component in visual surveillance systems. In this paper, we investigate gender classification from…”
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    Conference Proceeding
  20. 20

    Camera mote with a high-performance parallel processor for real-time frame-based video processing by Kleihorst, R., Abbo, A., Schueler, B., Danilin, A.

    “…This paper describes a new smart camera mote with a high performance SIMD (single-instruction multiple-data) processor. Previous versions of our camera mote…”
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    Conference Proceeding