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Beijing, China

Baidu百度, Inc. , incorporated on January 18, 2000, is a Chinese web services company headquartered in the Baidu Campus in Haidian District in Beijing.Baidu offers many services, including a Chinese language-search engine for websites, audio files, and images. Baidu offers 57 search and community services including Baidu Baike and a searchable, keyword-based discussion forum. Baidu was established in 2000 by Robin Li and Eric Xu. Both of the co-founders are Chinese nationals who studied and worked overseas before returning to China. In May 2014, Baidu ranked 5th overall in the Alexa Internet rankings. During Q4 of 2010, it is estimated that there were 4.02 billion search queries in China of which Baidu had a market share of 56.6%. China's Internet-search revenue share in second quarter 2011 by Baidu is 76%. In December 2007, Baidu became the first Chinese company to be included in the NASDAQ-100 index. In December 2014, Baidu was expected to invest in the company Uber.Baidu provides an index of over 740 million web pages, 80 million images, and 10 million multimedia files. Baidu offers multimedia content including MP3 music, and movies, and is the first in China to offer Wireless Application Protocol and personal digital assistant -based mobile search.Baidu Baike is similar to Wikipedia as an encyclopedia; however, unlike Wikipedia, only registered users can edit the articles. While access to Wikipedia has been intermittently blocked or certain articles filtered in China since June 2004, there is some controversy about the degree to which Baidu cooperates with Chinese government censorship. Wikipedia.


Huang C.,Baidu | Li Y.,Google | Nevatia R.,University of Southern California
IEEE Transactions on Pattern Analysis and Machine Intelligence | Year: 2013

We propose a hierarchical association approach to multiple target tracking from a single camera by progressively linking detection responses into longer track fragments (i.e., tracklets). Given frame-by-frame detection results, a conservative dual-threshold method that only links very similar detection responses between consecutive frames is adopted to generate initial tracklets with minimum identity switches. Further association of these highly fragmented tracklets at each level of the hierarchy is formulated as a Maximum A Posteriori (MAP) problem that considers initialization, termination, and transition of tracklets as well as the possibility of them being false alarms, which can be efficiently computed by the Hungarian algorithm. The tracklet affinity model, which measures the likelihood of two tracklets belonging to the same target, is a linear combination of automatically learned weak nonparametric models upon various features, which is distinct from most of previous work that relies on heuristic selection of parametric models and manual tuning of their parameters. For this purpose, we develop a novel bag ranking method and train the crucial tracklet affinity models by the boosting algorithm. This bag ranking method utilizes the soft max function to relax the oversufficient objective function used by the conventional instance ranking method. It provides a tighter upper bound of empirical errors in distinguishing correct associations from the incorrect ones, and thus yields more accurate tracklet affinity models for the tracklet association problem. We apply this approach to the challenging multiple pedestrian tracking task. Systematic experiments conducted on two real-life datasets show that the proposed approach outperforms previous state-of-the-art algorithms in terms of tracking accuracy, in particular, considerably reducing fragmentations and identity switches. © 1979-2012 IEEE. Source


Ji S.,Old Dominion University | Yang M.,Laboratories America Inc. | Yu K.,Baidu
IEEE Transactions on Pattern Analysis and Machine Intelligence | Year: 2013

We consider the automated recognition of human actions in surveillance videos. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. Convolutional neural networks (CNNs) are a type of deep model that can act directly on the raw inputs. However, such models are currently limited to handling 2D inputs. In this paper, we develop a novel 3D CNN model for action recognition. This model extracts features from both the spatial and the temporal dimensions by performing 3D convolutions, thereby capturing the motion information encoded in multiple adjacent frames. The developed model generates multiple channels of information from the input frames, and the final feature representation combines information from all channels. To further boost the performance, we propose regularizing the outputs with high-level features and combining the predictions of a variety of different models. We apply the developed models to recognize human actions in the real-world environment of airport surveillance videos, and they achieve superior performance in comparison to baseline methods. © 1979-2012 IEEE. Source


Patent
Baidu | Date: 2014-12-18

An information searching method and an information searching device are provided. The information searching method includes: receiving, at one or more computing devices, a first query from a client device, and obtaining, at the one or more computing devices an intention clarification guidance sentence according to the first query; receiving a second query updated according to the intention clarification guidance sentence; obtaining a search result according to the second query; and returning the search result to the client device.


An interactive searching and recommending method and apparatus are provided. The method includes following steps. A search query is received, a plurality of search results associated with the search query are obtained, the plurality of search results are analyzed so as to obtain at least one recommended item and a recommended content corresponding to the recommended item, a search webpage is provided and the plurality of search results and the at least one recommended item are displayed in the search webpage, and a triggering operation on the recommended item is received and the recommended content corresponding to the triggered recommended item is displayed within the search webpage according to the triggering operation.


An objective of the present invention is providing a method and apparatus for providing recommended information. A method according to the present invention comprises steps of: determining, based on one or more pieces of content information in one or more webpages, whether the one or more pieces of content information may be used as recommended information, respectively; obtaining feature information of the recommended information if the content information is recommended information; determining ordering information of the each piece of recommended information based on the feature information of each piece of recommended information; wherein the method further comprises the following step: if a users browsing operation on the webpage corresponds to at least one piece of recommended information, presenting the at least one piece of recommended information.

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