Visual tracking is important in computer vision. At present, although many algorithms of visual tracking have been proposed, there are still many problems which are needed to be solved, such as occlusion and frame speed. To solve these problems, this paper proposes a novel method which based on compressive tracking. Firstly, we make sure the occlusion happens if the testing result about image features by the classifiers is lower than a threshold value which is certain. Secondly, we mark the occluded image and record the occlusion region. In the next frame, we test both the classifier and the marked image. This algorithm makes sure the tracking is fast, and the result about solving occlusion is much better than other algorithms, especially compressive tracking.
Human action recognition and analysis is an active research topic in computer vision for many years. This paper presents a method to represent human actions based on trajectories consisting of 3D joint positions. This method first decompose action into a sequence of meaningful atomic actions (actionlets), and then label actionlets with English alphabets according to the Davies-Bouldin index value. Therefore, an action can be represented using a sequence of actionlet symbols, which will preserve the temporal order of occurrence of each of the actionlets. Finally, we employ sequence comparison to classify multiple actions through using string matching algorithms (Needleman-Wunsch). The effectiveness of the proposed method is evaluated on datasets captured by commodity depth cameras. Experiments of the proposed method on three challenging 3D action datasets show promising results.
Proc. SPIE. 9501, Satellite Data Compression, Communications, and Processing XI
KEYWORDS: Lithium, Data compression, Networks, Data acquisition, Distance measurement, Data communications, Global system for mobile communications, Information operations, Mobile communications, Data analysis
Collecting reliable and accurate MR data on time plays a vital role in the mobile communication network optimization. However, with the increment of the number of mobile users, network bandwidth cannot meet with mass transfer of MR. A high performance and high compression ratio GSM-MR compression algorithm is proposed to gain better transfer time. This algorithm utilizes two step sorting in order to reduce the distance between similar content, based on the analytic result about similarities of GSM-MR data sorting by different fields. Experimental results reveal that the algorithm does not only decrease compression consuming time, but also ascends compression ratio with the increment of the size of compression data.