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Optimized information processing in resource-constrained vision systems. From low-complexity coding to smart sensor networks

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Optimized information processing in resource-constrained vision systems. From low-complexity coding to smart sensor networks

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dc.contributor.advisor Prades Nebot, José es_ES
dc.contributor.advisor Philips, Wilfried es_ES
dc.contributor.advisor Aghajan, Hamid es_ES
dc.contributor.author MORBEE, MARLEEN es_ES
dc.date.accessioned 2011-10-14T11:47:42Z
dc.date.available 2011-10-14T11:47:42Z
dc.date.created 2011-03-31T08:00:00Z es_ES
dc.date.issued 2011-10-14T11:47:39Z es_ES
dc.identifier.uri http://hdl.handle.net/10251/12126
dc.description.abstract Vision systems have become ubiquitous. They are used for traffic monitoring, elderly care, video conferencing, virtual reality, surveillance, smart rooms, home automation, sport games analysis, industrial safety, medical care etc. In most vision systems, the data coming from the visual sensor(s) is processed before transmission in order to save communication bandwidth or achieve higher frame rates. The type of data processing needs to be chosen carefully depending on the targeted application, and taking into account the available memory, computational power, energy resources and bandwidth constraints. In this dissertation, we investigate how a vision system should be built under practical constraints. First, this system should be intelligent, such that the right data is extracted from the video source. Second, when processing video data this intelligent vision system should know its own practical limitations, and should try to achieve the best possible output result that lies within its capabilities. We study and improve a wide range of vision systems for a variety of applications, which go together with different types of constraints. First, we present a modulo-PCM-based coding algorithm for applications that demand very low complexity coding and need to preserve some of the advantageous properties of PCM coding (direct processing, random access, rate scalability). Our modulo-PCM coding scheme combines three well-known, simple, source coding strategies: PCM, binning, and interpolative coding. The encoder first analyzes the signal statistics in a very simple way. Then, based on these signal statistics, the encoder simply discards a number of bits of each image sample. The modulo-PCM decoder recovers the removed bits of each sample by using its received bits and side information which is generated by interpolating previous decoded signals. Our algorithm is especially appropriate for image coding. es_ES
dc.language Inglés es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.rights Reserva de todos los derechos es_ES
dc.source Riunet es_ES
dc.subject Vision systems es_ES
dc.subject Distributed video coding es_ES
dc.subject Sensor networks es_ES
dc.subject Smart cameras es_ES
dc.subject Occupancy sensing es_ES
dc.subject Resource-constrained systems es_ES
dc.subject Computer vision es_ES
dc.subject Task assignment es_ES
dc.subject Camera selection es_ES
dc.subject Image and video processing es_ES
dc.subject Image and video compression es_ES
dc.subject Wyner-ziv coding es_ES
dc.subject Low-complexity es_ES
dc.subject Line sensors es_ES
dc.subject Information processing es_ES
dc.subject.classification TEORIA DE LA SEÑAL Y COMUNICACIONES es_ES
dc.title Optimized information processing in resource-constrained vision systems. From low-complexity coding to smart sensor networks
dc.type Tesis doctoral es_ES
dc.identifier.doi 10.4995/Thesis/10251/12126 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.description.bibliographicCitation Morbee, M. (2011). Optimized information processing in resource-constrained vision systems. From low-complexity coding to smart sensor networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/12126 es_ES
dc.description.accrualMethod Palancia es_ES
dc.type.version info:eu-repo/semantics/acceptedVersion es_ES
dc.relation.tesis 3515 es_ES


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