Gan Zongliang

Compressed video super-resolution reconstruction based on regularized algorithm

Estimating high-resolution (HR) video from a sequence of low-resolution (LR) compressed observations is the focus of this paper. Based on the theory of regularization, this paper proposes a new form of regularized cost function to control the within-channel balance between received data and prior information, and a channel weight coefficient to control the cross-channel fidelity. The LR frames are adaptively weighted according to their reliability and the regularization parameter is simultaneously estimated for each channel with ameliorating artifacts in compressed video. An iterative gradient descent algorithm is utilized to reconstruction the HR video. Experimental results demonstrate that the proposed algorithm has an improvement in terms of both objective and subjective quality

Distributed adaptive compressed video sensing using smoothed projected landweber reconstruction

A novel Compressed-Sensing-based (CS-based) Distributed Video Coding (DVC) system, called Distributed Adaptive Compressed Video Sensing (DISACOS), is proposed in this paper. In this system, the input frames are divided into key frames and non-key frames, which are encoded by block CS sampling. The key frames are encoded as CS measurements at substantially higher rates than the non-key frames and decoded by the Smoothed Projected Landweber (SPL) algorithm using multi-hypothesis predictions. For the non-key frames, a small number of CS measurements are first transmitted to detect blocks having low-quality Side Information (SI) generated by the conventional interpolation or extrapolation at the decoder; then, another group of CS measurements are sampled again upon the decoders request. To fully utilise the CS measurements, we adaptively allocate these measurements to each block in terms of different edge features. Finally, the residual frame is reconstructed using the SPL algorithm and the decoded non-key frame is simply determined as the sum of the residual frame and the SI. Experimental results have revealed that our CS-based DVC system yields better rate-distortion performance when compared with other schemes.

A Fast PN Code Acquisition Algorithm for DS-UWB Systems

The great potential of the direct sequence ultra- wideband (DS-UWB) depends critically on the success of timing acquisition. In this paper, we present a rapid acquisition algorithm for reducing the acquisition time of the coarse pseudo-noise (PN) sequences with the auxiliary sequence and binary search strategy based on threshold comparison criterion. Both theoretical analysis and simulation tests show that with the proposed search strategy and simple operations over the symbol duration at the receiver, our algorithm can reduce considerably the acquisition time while maintain the PN sequence acquisition probability in DS-UWB system over dense multi-path environment.

Action recognition from a different view

In this paper, we propose a novel approach to recognise human activities from a different view. Although appearance-based recognition methods have been shown to be unsuitable for action recognition for varying views, there must be some regularity among the same action sequences of different views. Self-similarity matrices appear to be relative stable across views. However, the ability to effectively realise this stability is a problem. In this paper, we extract the shape-flow descriptor as the low-level feature and then choose the same number of key frames from the action sequences. Self-similarity matrices are obtained by computing the similarity between any pair of the key frames. The diagonal features of the similarity matrices are extracted as the highlevel feature representation of the action sequence and Support Vector Machines (SVM) is employed for classification. We test our approach on the IXMAS multi-view data set. The proposed approach is simple but effective when compared with other algorithms.