Modeling inter-camera space–time and appearance relationships for tracking across non-overlapping views

Javed, Omar; Shafique, Khurram; Rasheed, Zeeshan; Shah, Mubarak

doi:10.1016/j.cviu.2007.01.003

Cited by 274 publications

(242 citation statements)

References 21 publications

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“…A recent method for re-id is proposed by Farenzena et al (2010): it extracts features from different body parts, and weights them opportunely by exploiting symmetry and asymmetry perceptual principles. Other approaches, for example see Javed et al (2007), add temporal reasoning on the spatial layout of the monitored environment, but these cannot be considered purely appearance-based approaches.…”

Section: Introductionmentioning

confidence: 99%

Multiple-shot person re-identification by chromatic and epitomic analyses

Bazzani

Cristani

Perina

et al. 2012

Pattern Recognition Letters

162

113

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We propose a novel appearance-based method for person re-identification, that condenses a set of frames of an individual into a highly informative signature, called the Histogram Plus Epitome, HPE. It incorporates complementary global and local statistical descriptions of the human appearance, focusing on the overall chromatic content via histogram representation, and on the presence of recurrent local patches via epitomic analysis. The re-identification performance of HPE is then augmented by applying it as human part descriptor, defining a structured feature called Asymmetry-based HPE (AHPE). The matching between (A)HPEs provides optimal performances against low resolution, occlusions, pose and illumination variations, defining state-of-the-art results on all the considered datasets.

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Section: Introductionmentioning

confidence: 99%

Multiple-shot person re-identification by chromatic and epitomic analyses

Bazzani

Cristani

Perina

et al. 2012

Pattern Recognition Letters

162

113

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“…Different color channels and their combination can be used: the Hue channel from the HSV color space (Oliveira and Luiz, 2009); the Hue and Saturation channels jointly (Gheissari et al, 2006); or the three channels of the HSV color space (Farenzena et al, 2010). Also, the histogram of the RGB color space is widely used (Prosser et al, 2008;Javed et al, 2008;Cheng et al, 2009;Berdugo et al, 2010). A concatenation of histograms from RGB, YCbCr, and HS (from HSV) color channels (Fig.…”

Section: Featuresmentioning

confidence: 99%

“…Color is the most commonly used appearance feature encoded in the form of either histograms (Gheissari et al, 2006;Gray and Tao, 2008;Javed et al, 2008;Oliveira and Luiz, 2009;Cheng et al, 2009;Farenzena et al, 2010;Prosser et al, 2010;Kuo et al, 2010;Zheng et al, 2011) or cumulative histograms (Berdugo et al, 2010), which are simple to compute and scale invariant. Different color channels and their combination can be used: the Hue channel from the HSV color space (Oliveira and Luiz, 2009); the Hue and Saturation channels jointly (Gheissari et al, 2006); or the three channels of the HSV color space (Farenzena et al, 2010).…”

Section: Featuresmentioning

confidence: 99%

“…The third phase, cross-camera calibration, establishes the color and spatio-temporal relationship across cameras and allows to account for the variability of observations of the same person across different FOVs. Spatio-temporal calibration methods encapsulate information about the camera deployment, the spatial relationship between cameras, the entry/exit points in the scene, and the traveling time across cameras (Javed et al, 2008). Finally, the association of candidates across cameras matches different instances of the same person using the information extracted in the previous phases.…”

Section: Introductionmentioning

confidence: 99%

“…A video-based dataset is the Terrascope dataset (Jeong and Jaynes, 2008) that consists of nine indoor cameras where eight people walk and act in an office environment. Javed et al (Javed et al, 2008) presented a video-based dataset with three sequences composed of up to three cameras from indoor and outdoor scenarios with large illumination changes and up to four fully visible people. Finally, a more challenging dataset in terms of occlusions is that with three outdoor cameras where up to ten people walk alone or in small groups (Kuo et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Person re-identification in crowd

Mazzon

Tahir

Cavallaro

2012

Pattern Recognition Letters

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Person re-identification aims to recognize the same person viewed by disjoint cameras at different time instants and locations. In this paper, after an extensive review of state-of-the-art approaches, we propose a re-identification method that takes into account the appearance of people, the spatial location of cameras and potential paths a person can choose to follow. This choice is modeled with a set of areas of interest (landmarks) that constrain the propagation of people trajectories in non-observed regions between the field-of-view of cameras. We represent people with a selective patch around their upper body to work in crowded scenes when occlusions are frequent. We demonstrate the proposed method in a challenging scenario from London Gatwick airport and compare it to well-known person re-identification methods, highlighting their strengths and limitations. Finally, we show by Cumulative Matching Characteristic curve that the best performance results by modeling people movements in non-observed regions combined with appearance methods, achieving an average improvement of 6% when only appearance is used and 15% when only motion is used for the association of people across cameras.

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Person re‐identification with local descriptors across multicameras

Huang

Yang

2013

Computer Animation & Virtual

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Tracking the same person across multiple cameras is an important task in human motion analysis systems. It is also desirable to re‐identify the individuals who have been previously seen with a single camera. This paper addresses this problem by the re‐identification of the same individual in two different datasets, which are both challenging situations from human motion analysis systems. In this paper, local descriptors are introduced for image description, and support vector machines are employed for high classification performance and so an efficient bag‐of‐features approach for image presentation. In this way, robustness against low resolution, occlusion, and pose, viewpoint and illumination changes is achieved in a very fast way. We obtain promising results from the evaluation with situations where a number of individuals vary continuously from a multicamera system. Copyright © 2013 John Wiley & Sons, Ltd.

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Modeling inter-camera space–time and appearance relationships for tracking across non-overlapping views

Cited by 274 publications

References 21 publications

Multiple-shot person re-identification by chromatic and epitomic analyses

Multiple-shot person re-identification by chromatic and epitomic analyses

Person re-identification in crowd

Person re‐identification with local descriptors across multicameras

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