Outline Kulkarni, P., Ganesan, D., Shenoy, P., and Lu, Q. SensEye: a multi-tier camera sensor network. In Proceedings of the 13th Annual ACM international.

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Outline Kulkarni, P., Ganesan, D., Shenoy, P., and Lu, Q. SensEye: a multi-tier camera sensor network. In Proceedings of the 13th Annual ACM international Conference on Multimedia (Hilton, Singapore, November 06 - 11, 2005) Video sensing for environment monitoring: monitor wild-life habitats, rare species and phenology Ad-hoc surveillance Environment monitoring to track exotic animals Search and rescue missions Baby monitor (for toddlers)

System setup Use video sensors to track suspects Steps: Detect objects: know that an object is there Recognize objects: See if it interesting Track objects: Track its motion Approach 1: Single tier One sensor that can perform all the tasks Approach 2: Multi-tier Three tiers in this paper where each tier has increasing amounts of resources. Judiciously mix these tiers to achieve overall benefits Constraints: Cost (reliability and coverage) and energy consumption

Architecture

Design principles: Map each task to the least powerful tier with sufficient resources (and conseve energy) Exploit wakeup-on-demand higher tiers: (to conserve energy) Exploit redundancy in coverage: If two camera can see the same object, then use this fact to localize the object in order to wake up the smallest set of higher tier nodes Presumes good localization and calibration Lower tiers need to know where the higher tiers can see. Otherwise you need to enable every sensor

Tier 1 Lowest capability: Can perform object detection by using differencing between two frames (reference?) CMUcam + mote: 136 ms (132 for camera), 13.4 J for mote and 153.8 J for camera Cyclops + mote: 892 ms, 29.5 J Integrated platforms could be even more energy efficient

Tier 2 Stargate Webcam Latency to start capture is important

Tier 3 PTZ (Pan-Tilt-Zoom camera) linked to a mini-ITX embedded PC

Comparison Multi-tier architecture is far more energy efficient with almost similar recognition ratios

Discussion The claim is not that they invented new recognition algorithms On the other hand, we need recognition algorithms which may not be as accurate as the state of the art but can fit into small devices and run for long durations How good is this approach for ad-hoc surveillance Calibration and localization requirements What about latency based mis-recognition? Are PTZ cameras wired or on battery?