Agent-based moving object correspondence using differential discriminative diagnosis

Saptharishi, Mahesh; Hampshire, J.B.; Khosla, Pradeep K.

doi:10.1109/cvpr.2000.854936

Cited by 14 publications

(20 citation statements)

References 16 publications

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“…Most surveillance systems [1][2][3] [4] have found background subtraction to be an efficient means of motion detection with a stationary camera. Our basic algorithm is similar to those described in [2], [3] and [4].…”

Section: Motion Detectionmentioning

confidence: 99%

“…We show that training an agent to correspond an object offline and giving it the capability to customize itself to the object on-line, leads to an efficient correspondence algorithm. A detailed description of this algorithm is provided in [1].…”

Section: A Related Approachesmentioning

confidence: 99%

“…This maximization can be done efficiently online [1]. At each time instant we associate instances of an object in the scene that have the minimum relevance differential , , n i j ℜ using the relevance matrix i R that is unique to each object in the scene.…”

Section: B Discriminative Diagnosismentioning

confidence: 99%

“…Surveillance cameras are typically fixed at known positions and cover a circumscribed area defined by the fields of view of the cameras. Although some recent vision work has addressed autonomous surveillance [1] [2][3] [4], in most cases humans perform the sensory processing, either in real time, or by reviewing footage.…”

Section: Introductionmentioning

confidence: 99%

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Distributed surveillance and reconnaissance using multiple autonomous ATVs: CyberScout

Saptharishi

Oliver

Diehl

et al. 2002

IEEE Trans. Robot. Automat.

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Abstract-The objective of the CyberScout project is to develop an autonomous surveillance and reconnaissance system using a network of all-terrain vehicles. In this paper, we focus on two facets of this system: 1) vision for surveillance and 2) autonomous navigation and dynamic path planning.In the area of vision-based surveillance, we have developed robust, efficient algorithms to detect, classify, and track moving objects of interest (person, people, or vehicle) with a static camera. Adaptation through feedback from the classifier and tracker allow the detector to use grayscale imagery, but perform as well as prior color-based detectors. We have extended the detector using scene mosaicing to detect and index moving objects when the camera is panning or tilting. The classification algorithm performs well (less than 8% error rate for all classes) with coarse inputs (20x20-pixel binary image chips), has unparalleled rejection capabilities (rejects 72% of spurious detections), and can flag novel moving objects. The tracking algorithm achieves highly accurate (96%) frame-to-frame correspondence for multiple moving objects in cluttered scenes by determining the discriminant relevance of object features.We have also developed a novel mission coordination architecture, CPAD (Checkpoint/Priority/Action Database), which performs path planning via checkpoint and dynamic priority assignment, using statistical estimates of the environment's motion structure. The motion structure is used to make both preplanning and reactive behaviors more efficient by applying global context. This approach is more computationally efficient than centralized approaches and exploits robot cooperation in dynamic environments better than decoupled approaches.

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Section: Motion Detectionmentioning

confidence: 99%

Section: A Related Approachesmentioning

confidence: 99%

Section: B Discriminative Diagnosismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Distributed surveillance and reconnaissance using multiple autonomous ATVs: CyberScout

Saptharishi

Oliver

Diehl

et al. 2002

IEEE Trans. Robot. Automat.

Self Cite

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“…The object is detected by comparing current camera image with the corresponding background indexed from the mosaic. In [6], a novel method is proposed by Saptharishi et al for temporally and spatially moving objects by automatically learning the relevance of the object's appearance features to the task of discrimination. This method is proposed for distributed surveillance systems.…”

Section: Literature Reviewmentioning

confidence: 99%

VISTA: achieving cumulative VIsion through energy efficient Silhouette recognition of mobile Targets through collAboration of visual sensor nodes

et al. 2014

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Visual sensor networks (VSNs) are innovative networks founded on a broad range of areas such as networking, imaging, and database systems. These networks demand well-defined architectures in terms of sensor nodes and camera deployment, image capturing and processing, and well-organized distributed systems. This makes existing VSN architectures deficient because these are limited in approach and in design. In this paper, we propose VISTA, a distributed vision multi-layer architecture aimed at constructing the cumulative vision of mobile objects (MOs). VISTA realizes silhouette recognition of mobile targets through (a) pre-meditated deployment of sensor nodes (SNs) that are equipped with sonar sensors and fixed view (FV) on-board cameras present at the periphery of region of interest (RoI) and SNs with only on-board cameras within RoI, (b) pre-distribution of silhouettes of known objects across SNs, (c) sonar-based presence detection of MO at the outskirts of RoI, (d) MO silhouette capturing and matching at interior node to determine the % age match, (e) subsequent activation of next interior cameras in order to improve % age match, and (f) terminating further activation upon threshold recognition of MO. Experimental evaluation of our image processing algorithms against baseline algorithms with respect to execution time and memory shows significant reduction in image data and memory occupancy. Also, experiments show that true match is achieved fully under broad daylight conditions and large backgrounds when our proposed background subtraction and pixel reduction techniques are used. The mobility-driven behavior of associated network layer algorithms of VISTA is simulated in a network simulator (NS2) by representing the surety of MO identification as a function of number of cameras, database size and distribution, MO's trajectory, stored perspectives, and network depth. The simulation results show that doubling and, in some situations, manifold increase is observed in the surety of the target with an increase in the number of silhouettes deployed against the baselined database size and mobility model. The results substantiate that VISTA is a suitable architecture for low-cost, autonomous and efficient human and asset monitoring surveillance, friend-or-foe (FoF) identification, and target tracking systems.

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Motion analysis for event detection and tracking with a mobile omnidirectional camera

Gandhi

Trivedi

2004

Multimedia Systems

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Abstract.A mobile platform mounted with omnidirectional vision sensor (ODVS) can be used to monitor large areas and detect interesting events such as independently moving persons and vehicles. To avoid false alarms due to extraneous features, the image motion induced by the moving platform should be compensated. This paper describes a formulation and application of parametric egomotion compensation for an ODVS. Omni images give 360• view of surroundings but undergo considerable image distortion. To account for these distortions, the parametric planar motion model is integrated with the transformations into omni image space. Prior knowledge of approximate camera calibration and camera speed is integrated with the estimation process using a Bayesian approach. Iterative, coarse-to-fine, gradient-based estimation is used to correct the motion parameters for vibrations and other inaccuracies in prior knowledge. Experiments with a camera mounted on various types of mobile platforms demonstrate successful detection of moving persons and vehicles.

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Agent-based moving object correspondence using differential discriminative diagnosis

Abstract: We

Cited by 14 publications

References 16 publications

Distributed surveillance and reconnaissance using multiple autonomous ATVs: CyberScout

Distributed surveillance and reconnaissance using multiple autonomous ATVs: CyberScout

VISTA: achieving cumulative VIsion through energy efficient Silhouette recognition of mobile Targets through collAboration of visual sensor nodes

Motion analysis for event detection and tracking with a mobile omnidirectional camera

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