Title :
Exploring Tradeoffs in Accuracy, Energy and Latency of Scale Invariant Feature Transform in Wireless Camera Networks
Author :
Ko, Teresa ; Charbiwala, Zainul M. ; Ahmadian, Shaun ; Rahimi, Mohammad ; Srivastava, Mani B. ; Soatto, Stefano ; Estrin, Deborah
Author_Institution :
California Univ., Los Angeles
Abstract :
Advances in DSP technology create important avenues of research for embedded vision. One such avenue is the investigation of tradeoffs amongst system parameters which affect the energy, accuracy, and latency of the overall system. This paper reports work on benchmarking the performance and cost of scale invariant feature transform (SIFT) for visual classification on a Blackfin DSP processor. Through measurements and modeling of the camera sensor node, we investigate system performance (classification accuracy, latency, energy consumption) in light of image resolution, arithmetic precision, location of processing (local vs. server-side), and processor speed. A case study on counting eggs during avian nesting season is used to experimentally determine the tradeoffs of different design parameters and discuss implications to other application domains.
Keywords :
digital signal processing chips; video cameras; wireless sensor networks; Blackfin DSP processor; DSP; SIFT; avian nesting season; camera sensor node; egg counting; embedded vision; object recognition; scale invariant feature transform; system tradeoffs; visual classification; wireless camera networks; Cameras; Costs; Delay; Digital signal processing; Energy consumption; Energy measurement; Image resolution; Image sensors; Sensor systems; System performance; DSP; SIFT; embedded vision; object recognition; system tradeoffs;
Conference_Titel :
Distributed Smart Cameras, 2007. ICDSC '07. First ACM/IEEE International Conference on
Conference_Location :
Vienna
Print_ISBN :
978-1-4244-1354-6
Electronic_ISBN :
978-1-4244-1354-6
DOI :
10.1109/ICDSC.2007.4357539