Multi-camera multi-person tracking for EasyLiving

Krumm, John; Harris, Steve; Meyers, Brian; Brumitt, Barry; Hale, Mike; Shafer, Steven A.

doi:10.1109/vs.2000.856852

Cited by 511 publications

(284 citation statements)

References 18 publications

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“…The floor contains force measuring load cells. In [3], [7] and [9] they use computer vision in order to track several persons in real-time. The persons' location in the room is established based on a combination of knowledge of the cameras' relative location, fields of view of the cameras and heuristics on the movements of people.…”

Section: Indoor Person Presence Detectionmentioning

confidence: 99%

Applications of Vision-Based Attention-Guided Perceptive Devices to Aware Environments

Raducanu

Markopoulos

2003

Lecture Notes in Computer Science

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Abstract. This paper discusses a computer vision based approach for enhancing a physical environment with machine perception. Using techniques for assessing the distance and orientation of a target from the camera, we detect user presence and estimate whether an object of interest is the focus of attention of the user. Our solution uses low-cost cameras and is designed to be robust to lighting variations typical of home and work environments. We argue why this approach is a useful component for the incremental construction of aware environments and discuss some practical applications of using such a system.

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Section: Indoor Person Presence Detectionmentioning

confidence: 99%

Applications of Vision-Based Attention-Guided Perceptive Devices to Aware Environments

Raducanu

Markopoulos

2003

Lecture Notes in Computer Science

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“…Other relevant applications are advanced visual interfaces for context-aware applications (Koller et al 1997;Krumm et al 2000) and video mining systems to retrieve and understand situations for statistical analysis of, for example, sports, physical performance of players, semantic analysis, etc. (Xu et al 2004;Liu et al 2009;Joo et al 2007).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy region assignment for visual tracking

et al. 2011

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In this work we propose a new approach based on fuzzy concepts and heuristic reasoning to deal with the visual data association problem in real time, considering the particular conditions of the visual data segmented from images, and the integration of higher-level information in the tracking process such as trajectory smoothness, consistency of information, and protection against predictable interactions such as overlap/occlusion, etc. The objects' features are estimated from the segmented images using a Bayesian formulation, and the regions assigned to update the tracks are computed through a fuzzy system to integrate all the information. The algorithm is scalable, requiring linear computing resources with respect to the complexity of scenarios, and shows competitive performance with respect to other classical methods in which the number of evaluated alternatives grows exponentially with the number of objects.

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“…In [19] it is applied to augment a background colour intensity model to obtain foreground regions. These foreground pixels are clustered together into blob regions of discrete disparity bounds, and finally the blobs are clustered into people-shaped regions by searching through the space of possible groupings.…”

Section: Introductionmentioning

confidence: 99%

Robust pedestrian detection and tracking in crowded scenes

Kelly

O’Connor

Smeaton

2009

Image and Vision Computing

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In this paper, a robust computer vision approach to detecting and tracking pedestrians in unconstrained crowded scenes is presented. Pedestrian detection is performed via a 3D clustering process within a region-growing framework. The clustering process avoids using hard thresholds by using bio-metrically inspired constraints and a number of plan view statistics. Pedestrian tracking is achieved by formulating the track matching process as a weighted bipartite graph and using a Weighted Maximum Cardinality Matching scheme. The approach is evaluated using both indoor and outdoor sequences, captured using a variety of different camera placements and orientations, that feature significant challenges in terms of the number of pedestrians present, their interactions and scene lighting conditions. The evaluation is performed against a manually generated groundtruth for all sequences. Results point to the extremely accurate performance of the proposed approach in all cases.

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Multi-camera multi-person tracking for EasyLiving

Cited by 511 publications

References 18 publications

Applications of Vision-Based Attention-Guided Perceptive Devices to Aware Environments

Applications of Vision-Based Attention-Guided Perceptive Devices to Aware Environments

Fuzzy region assignment for visual tracking

Robust pedestrian detection and tracking in crowded scenes

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