An new object oriented development suite for data fusion is presented. It is shown how the various issues in the data fusion development like design, implementation, simulation and testing may be supported. This allows the realisation of high sophisticated data fusion systems as applied in numerous civil and defence areas: e.g. air traffic control, coastal surveillance, vehicle guidance systems...

GM-APDæ¿€å ‰é›·è¾¾å ·æœ‰å•å ‰å­æŽ¢æµ‹çµæ•åº¦ï¼Œå¤§å¹ é™ä½Žäº†ç³»ç»Ÿä½“ç§¯å’ŒåŠŸè€—ï¼Œä½†å—åƒå ƒæ•°é™åˆ¶ï¼Œéš¾ä»¥èŽ·å¾—è¿œè·ç¦»å°ç›®æ ‡æ¸ æ™°è½®å»“ï¼Œç›®æ ‡æ£€æµ‹çŽ‡ä¸é«˜ã€‚é’ˆå¯¹è¯¥é—®é¢˜ï¼Œæå‡ºäº†åŸºäºŽå¼ºåº¦åƒå’Œè·ç¦»åƒå¤šçº§å¤„ç†çš„å°ç›®æ ‡æ·±åº¦å­¦ä¹ æ£€æµ‹ç®—æ³•ï¼Œå åˆ†æŒ–æŽ˜å¼ºåº¦å›¾åƒå’Œç‚¹äº‘ç‰¹å¾ä¿¡æ¯åŠç›¸äº’å ³è”æ€§ï¼Œæé«˜å°ç›®æ ‡æ£€æµ‹æ¦‚çŽ‡ã€‚é€šè¿‡æ”¹è¿›ç‰...

Decision templates (DT) are a technique for classifier fusion for continuous-valued individual classifier outputs. The individual outputs considered here sum up to the same value (e.g., statistical classifiers, yielding some estimates of the posterior probabilities for the classes). First, the DT fusion algorithm is explained. Second, we show that two similarity measures (S1 and S2) and two inc...

Object segmentation aims to perfectly identify objects embedded in the surrounding environment and has a wide range of applications. Most previous methods object only use RGB images ignore geometric information from disparity images. Making full heterogeneous data different devices proved be very effective strategy for improving performance. The key challenge multimodal fusion based task lies l...

In the process of object-oriented change detection, the determination of the optimal segmentation scale is directly related to the subsequent change information extraction and analysis. Aiming at this problem, this paper presents a novel object-level change detection method based on multi-scale segmentation and fusion. First of all, the fine to coarse segmentation is used to obtain initial obje...

In this paper we study the problem of Bayesian sensor fusion for dynamic object tracking. The prospects of utilizing measurements from several sensors to infer about a system state are manyfold and they range from increased estimate accuracy to more reliable and robust estimates. Sensor measurements may be combined, or fused, at a variety of levels; from the raw data level to a state vector lev...

We examine the use of fusing data from multiple data sources for use within object recognition systems. We then continue, to illustrate the system that we have created for our own object recognition needs. The data fusion model that we use is embedded within an object recognition system that analyses simulated FLIR and LADAR data to recognise and track aircraft. The data fusion is based upon th...

Object tracking is very important for automatic indexing of video content. This work shows tracking of objects directly using compressed MPEG video data. Two sensors, one using motion vectors and the other using DCT coefficients obtained from compressed video stream, provide measurements for the location of the object being tracked. The optimal estimate from the two measurements is found using ...

We develop a symbolic computational approach to classifying lowrank modular fusion categories, up to finite ambiguity. By a generalized form of Ocneanu rigidity due to Etingof, Ostrik and Nikshych, it is enough to classify modular fusion algebras of a given rank–that is, to determine the possible Grothendieck rings with modular realizations. We use this technique to classify modular categories ...